Should you upgrade to ChatGPT Pro, use Claude or just keep using GPT 4o?
OpenAI’s GPT-4.5 and Anthropic’s Claude 3.7 are two cutting-edge large language models that have recently been released. Both claim improvements over their predecessors, but they have different strengths and target use cases. Below, we compare GPT-4.5 and Claude 3.7 based on online opinions and official information, focusing on four key areas: developers (coding and debugging), email-heavy users (productivity and writing assistance), pricing, and general user opinions.
Coding Capabilities: GPT-4.5 is positioned as an incremental upgrade in general knowledge and writing, but it does not dramatically improve reasoning-heavy tasks like complex coding or math. Early testers (including Andrej Karpathy) noted that GPT-4.5 “does not push forward model capability in cases where reasoning is critical (math, code, etc.)”. In practice, GPT-4.5’s coding performance is only slightly better than GPT-4, and it remains weaker at coding than specialized reasoning models.
On an internal benchmark for fixing code (SWE-Bench), GPT-4.5 scored about 38%, trailing far behind OpenAI’s own reasoning-focused model o3-mini (around 61%) (GPT-4.5 | Hacker News). Some developers on forums observed that GPT-4.5 is “a bit better at coding than ChatGPT 4o (GPT-4 original) but not better than o3-mini”. By contrast, Claude 3.7 is known for strong coding skills.
Anthropic calls Claude 3.7 “state-of-the art for coding,” claiming it achieves 70.3% on a competitive coding benchmark (SWE-Bench in standard mode) – the highest among its models . Users frequently report that Claude 3.7 “smokes” GPT models on coding tasks, especially for generating larger codebases or understanding complex code context.
Debugging and Reasoning: Claude 3.7 introduced an “extended thinking” mode that lets it perform step-by-step reasoning before answering. This is essentially chain-of-thought reasoning visible to the user, useful for complex problem solving and debugging logic errors. In extended mode, Claude can analyze code and problems in-depth, leading to more accurate solutions for tough bugs or algorithmic challenges (at the cost of using more tokens and taking slightly longer).
GPT-4.5, on the other hand, is a non-chain-of-thought model – it generates direct answers without an explicit step-by-step reasoning process. This makes GPT-4.5 faster per query, but it can be “oddly lazy on complex projects” that require careful multi-step planning. Developers have found that GPT-4.5 might miss some intricate bugs or logical steps because it doesn’t internally traverse the solution step by step as Claude can. In practice, Claude 3.7 often catches mistakes or offers stepwise corrections, making it adept at debugging code with explanations.
Claude is even reported to “recognize and correct its own mistakes” in code generation tasks, which is a valuable trait for debugging. GPT-4.5 can certainly assist with coding (e.g. suggest fixes or improvements), but if the problem is complex, it might give an answer that needs more manual verification.
As one AI commentator quipped, Claude 3.7 feels like GPT-4.5 when it comes to tough reasoning tasks, while GPT-4.5 behaves more like a Claude-style writer – highlighting that Claude didn’t sacrifice reasoning ability even as it improved creative output.
AI-Assisted Developer Tools: Anthropic has rolled out a dedicated tool called Claude Code, a command-line AI assistant for coding . This tool (in limited preview) allows developers to integrate Claude 3.7 into their workflow – you can invoke Claude directly from your terminal to generate code, refactor, or debug using natural language commands. The goal is to let Claude handle substantial engineering tasks as an “agentic” coding assistant, working with your codebase and toolchain.
Early users find that Claude Code can streamline coding workflows by delegating boilerplate coding or debugging tasks to the AI and then refining the results. On the GPT side, OpenAI hasn’t released an official CLI coding assistant, but developers can use GPT-4.5 via the API or in IDE integrations. For instance, tools like GitHub Copilot (powered by earlier OpenAI models) and third-party plugins in VS Code or JetBrains IDEs can connect to OpenAI’s API to offer code completions and fix suggestions. GPT-4.5 supports function calling and tool usage via API, so it can be integrated into developer agents that perform actions (like running code or tests) if developers set that up.
However, this requires custom development; OpenAI’s out-of-the-box offering for coding remains the ChatGPT interface and some plugin integrations. In summary, Claude 3.7 provides a more tailored coding assistant experience out-of-the-box (with its Claude Code tool and extended reasoning for debugging), whereas GPT-4.5 provides a strong foundation that can be built into developer tools, but with less specialized support for stepwise coding tasks.
If your work involves a lot of coding, debugging, or reading large codebases, many users suggest Claude 3.7 may be more helpful. Its large context window and reasoning mode allow it to ingest extensive code (or error logs) and walk through solutions methodically. Claude 3.7 has been “best-in-class for real-world coding” in early tests, producing production-ready code with minimal errors.
GPT-4.5 is no slouch and has improved slightly over GPT-4 in coding, but it shines more in content generation and straightforward tasks. It can certainly assist in coding (OpenAI notes GPT-4.5 is “useful for tasks like improving writing, programming, and solving practical problems”, but developers might use it more for generating snippets or explaining code rather than relying on it for complex algorithmic problem-solving. Notably, GPT-4.5’s writing style is more natural and human-like, which can help when generating documentation or code comments.
In contrast, Claude’s strength is handling complexity and large context, making it better at tasks like analyzing an entire code repository or debugging a deeply nested issue. Many developers end up using both: GPT-4.5 for its creativity and clarity in explanations, and Claude 3.7 when they need depth, longer context, or a second pair of eyes on tough code.
For professionals who live in their inbox, both GPT-4.5 and Claude 3.7 can act as powerful email assistants, but they have slightly different advantages.
GPT-4.5 is explicitly touted for communication tasks — one of its highlighted applications is “streamlined communication”: drafting professional emails, managing follow-ups, and helping schedule meetings. Thanks to its improved natural language ability and “emotional intelligence,” GPT-4.5 produces emails that read polished and human-like, with nuanced tone control. Early users report that GPT-4.5’s writing “doesn’t read like AI output anymore”.
It can capture a desired tone (e.g. formal, friendly, persuasive) and generate emails that need minimal editing. For someone dealing with dozens of emails a day, GPT-4.5 can save time by drafting replies or summarizing long threads into key points with action items. Its creativity also helps in phrasing things diplomatically or finding alternative wording, which can be useful in sensitive communications.
Claude 3.7 is also a strong writing assistant, with Anthropic noting significant improvements in content generation and planning in this version. One of Claude’s killer features for email-heavy users is its context length. Claude 3.7 supports an extremely large context window (up to ~200K tokens in the latest version) for input + output.
This means you can feed entire email threads, long documents, or multiple attachments into Claude and get a coherent summary or a contextual response. For instance, a user could provide Claude with a lengthy email chain (tens of thousands of words) and ask for a summary or a drafted reply that references specific details from earlier in the thread – something GPT-4.5 might struggle with if it exceeds its context limit (GPT-4.5’s context is likely similar to GPT-4’s, in the tens of thousands of tokens at most).
Claude 3.7 “can produce responses up to 128,000 tokens long – 15 times longer than its predecessor”, allowing far more detail when needed . This ability to handle and remember long conversations makes Claude very adept at maintaining continuity in email threads, preventing it from forgetting earlier details or instructions (a common pain point with smaller-context models). In fact, some users have said “nothing can match Claude's continuity” for long, detailed discussions.
Both models excel at generating well-structured, grammatically correct text, but users note subtle differences in style. GPT-4.5 tends to be extremely fluent and “creative” in wording, often producing a variety of phrasings that sound natural. It also has a higher “EQ” (emotional intelligence) according to OpenAI – meaning it can adjust the tone and empathy in writing, which is useful for customer-facing emails or delicate communications.
Claude’s writing is typically very clear and polite (Anthropic trains it with a focus on helpfulness and harmlessness). In earlier versions, Claude sometimes had a more verbose or formal style, but with Claude 3.7 it has become more concise and “upgraded” in its content generation. One professor noted after Claude’s update that it was capable of more free-form, less stilted responses – “Claude unchained!”, as he put it, describing a more engaging, less overly cautious style. For everyday emails, both can produce solid drafts; GPT-4.5 might give a bit more flair or warmth in phrasing, whereas Claude might stick closer to a factual, to-the-point summary (unless prompted otherwise).
Privacy and Security Considerations: When using AI to compose emails (which often contain sensitive or personal information), privacy is crucial. OpenAI and Anthropic both state that they do not use API data to train their models by default, which is important for business users. OpenAI clarified in 2023 that API usage won’t be used for model improvement unless you opt-in, and it launched ChatGPT Enterprise with guarantees of data encryption and no data retention beyond 30 days. Anthropic similarly promises not to use client-provided data from Claude for training unless a user explicitly flags it for feedback (I want to opt out of my prompts being used for training ...). In other words, if you use Claude via the API or Claude Pro, your inputs/outputs won’t end up in Anthropic’s training sets (barring abuse reporting). For everyday users, Claude offers a free tier and paid plans in a chat interface (claude.ai), and Anthropic’s privacy policy suggests that even chats on their platform are not used to retrain models unless you choose to give feedback. OpenAI’s ChatGPT (for Plus/Pro users) gives the option to turn off chat history, which ensures those conversations aren’t used in training data.
However, one should note that GPT-4.5 is initially only available to ChatGPT “Pro” subscribers (and API), and presumably Pro users’ conversations might be used by OpenAI to refine the model since GPT-4.5 is a research preview. OpenAI has invited feedback on GPT-4.5 to decide if it provides unique value. For corporate or email use where confidentiality is paramount, using the API or enterprise solutions of either provider is the safer route. ChatGPT Enterprise and Claude Enterprise both offer SOC 2 compliance and stricter data privacy.
Another aspect of security is how the models handle sensitive content in prompts/emails. Anthropic has a strong focus on AI safety with its “Constitutional AI” approach, meaning Claude is trained to refuse or safely handle harmful or confidential requests. Claude might be slightly more conservative in responses – for example, if an email draft might accidentally include sensitive personal data or problematic language, Claude could sanitize or warn about it. GPT-4.5 also has OpenAI’s refined safety filters, and with its broader knowledge base it may incorporate more up-to-date policy adherence. In general, both models are considered enterprise-grade in security, but Anthropic explicitly markets Claude as “trained to be safe, honest, and harmless” for workplace tasks. For an email-heavy user, this means Claude is unlikely to produce inappropriate content or leak information from prior parts of the conversation.
GPT-4.5’s improvements in reducing hallucinations (it hallucinated significantly less than GPT-4 in tests) also add to trustworthiness – you don’t want your AI assistant making up facts in a business email.
It’s worth noting where these models might be integrated for email workflows. GPT-4.5 can be accessed in ChatGPT’s interface or via API, and we’re seeing it used in products like Microsoft’s **Copilot for Outlook (Microsoft 365 Copilot uses GPT-4 to summarize and draft emails inside Outlook). As GPT-4.5 becomes available via API, similar integrations will use it for even better results. Claude, on the other hand, has partnerships too – for example, Claude is available in tools like Slack (Claude can be added to Slack to summarize channels or answer questions) and through providers like Quora’s Poe or AWS Bedrock for custom integrations. A savvy email user could connect Claude 3.7 to their email via an API script to, say, summarize unread messages every morning or draft replies based on bullet points. Thanks to Claude’s large context, it could summarize an entire day’s worth of email threads in one go.
GPT-4.5 can also do email summarization and drafting (and faster), but one may need to chunk very large volumes of text due to context limits. In practical terms, both models can dramatically enhance an email-heavy workflow – saving time on writing and reading – and both providers seem mindful of privacy (neither wants to scare away business users). The choice might come down to whether you need Claude’s long-document handling and step-by-step detail, or GPT-4.5’s more fluid writing style and integration in tools you already use.
One of the starkest differences between GPT-4.5 and Claude 3.7 is in pricing and how each model is made available. Below we break down the pricing for different usage levels, from casual users to heavy API users, as well as subscription options:
Subscription Plans (Chat Interfaces):
GPT-4.5: OpenAI initially released GPT-4.5 as a research preview available to ChatGPT Pro subscribers at $200 per month. This is a steep price aimed at professionals and enterprises; it offers priority access to GPT-4.5’s capabilities in ChatGPT. (OpenAI has a $20/mo ChatGPT Plus, but at launch Plus users did not get GPT-4.5 – only GPT-4.0 and older models. OpenAI indicated GPT-4.5 would roll out to Plus, Team, Enterprise, and Education plans in the future, but on day one it was gated behind the higher-tier plan.) There is no free tier for GPT-4 or 4.5 on ChatGPT – free users are limited to GPT-3.5. Essentially, to use GPT-4.5 interactively, you must pay for at least ChatGPT Pro ($200/mo) or access it via the API (which itself will incur usage costs discussed below).
Claude 3.7: Anthropic offers Claude through its own website and app with a more generous approach. Claude 3.7 is available on all Claude plans, including the Free tier. The free tier lets users try Claude 3.7 in standard mode (with some daily message limits). Paid plans include Claude Pro ($20/month) and Claude Team ($30/user/month), which offer higher usage limits and priority, and Claude Enterprise (custom pricing) for organizational use. Notably, Claude Pro at $20/mo is analogous in cost to ChatGPT Plus, but it does include the latest model (3.7) and even extended reasoning mode. In contrast to GPT-4.5’s paywall, Anthropic gave everyone from free users to enterprise access to Claude 3.7 upon release (only the extended reasoning mode is excluded from the free tier due to its heavy compute). This means a power user could be paying just $20 a month and still use Claude 3.7 for drafting emails or coding, whereas for GPT-4.5 the comparable capability would require the $200 plan or paying per API call.
Both OpenAI and Anthropic allow developers to use these models via API, charging based on token usage (where 1 token is roughly 3/4 of a word). Here the price difference is dramatic:
GPT-4.5 API pricing is significantly higher than previous models. According to OpenAI’s official rates (as shared with developers), GPT-4.5 costs $75 per 1M input tokens and $150 per 1M output tokens. In more familiar terms, that is $0.075 per 1,000 input tokens and $0.15 per 1,000 output tokens. By comparison, the original GPT-4 (8k context, “GPT-4o”) was about $0.03 per 1,000 input and $0.06 per 1,000 output tokens – so GPT-4.5 is well over 2x the price of GPT-4. It’s even more striking compared to smaller models: GPT-3.5-turbo, for instance, is only ~$0.002 per 1,000 tokens. The high cost of GPT-4.5 reflects its enormous size and compute needs. In fact, OpenAI themselves acknowledged the pricing is “insane” and that they’re evaluating if they will continue offering GPT-4.5 long-term given the expense. For heavy users, this cost can add up quickly. Example: A 1000-token prompt and a 1000-token completion (750 words each, a long email or code review) would cost about $0.075 + $0.15 = $0.225 per query. 100 such queries (100 long answers) would be $22.5. So a developer using GPT-4.5 extensively could rack up a big bill. (OpenAI does offer volume discounts or prefer usage via the $200/mo plan for those who can.)
Claude 3.7 API pricing is much lower. Anthropic kept the same rate as Claude 3.5’s API: $3 per 1M input tokens and $15 per 1M output tokens. That equates to $0.003 per 1,000 input tokens and $0.015 per 1,000 output tokens. This is literally 50× cheaper for inputs and 10× cheaper for outputs than GPT-4.5’s rates. Using the same example as above (1k in, 1k out, total 2k tokens): the Claude API call would cost $0.003 + $0.015 = $0.018. So you could roughly get 12 similar Claude responses for the price of one GPT-4.5 response in terms of token billing. Moreover, Anthropic offers features like prompt caching and batch processing that can reduce costs further (up to 90% off for cache hits, and 50% off for batched requests). Claude’s pricing strategy clearly aims to be developer-friendly and scalable. As one HN user pointed out, “Claude 3.7 Sonnet is doubly impressive at $3 / 1M tokens”, delivering high-quality results for a fraction of the cost.
To illustrate the pricing differences, consider the token costs side-by-side:
| Model API | Input Cost | Output Cost | Notes |
|---|---|---|---|
| GPT-4.5 | $75.00 per 1M tokens | $150.00 per 1M tokens | ( ~$0.075 / 1k input, $0.15 / 1k output ) |
| Claude 3.7 Sonnet | $3.00 per 1M tokens | $15.00 per 1M tokens | ( ~$0.003 / 1k input, $0.015 / 1k output ) |
Different Usage Levels:
It’s also worth noting that OpenAI might adjust GPT-4.5’s pricing or availability if it remains an “odd, expensive” model. They even hinted that they are “evaluating whether to continue serving it in the API long-term” due to the cost-benefit concerns. So, pricing could evolve. On the Anthropic side, their strategy seems to be offering powerful models at low cost to gain adoption, possibly subsidized by big partnerships (like with AWS). Right now, for anyone price-sensitive, Claude 3.7 offers far more bang for the buck in terms of API usage.
The AI community has been abuzz about GPT-4.5 vs Claude 3.7. Here we summarize the sentiment from forums like Reddit and Hacker News, as well as insights from AI experts and the companies themselves:
Incremental vs. Significant Improvement: A common theme is that GPT-4.5, while better than GPT-4, is an evolution, not a revolution. Andrej Karpathy likened the jump from GPT-4 to 4.5 to the subtle boost from GPT-3.5 to 4 – “everything is a little bit better… not trivial to point to”. Many users echo this, saying GPT-4.5’s responses feel more natural and it hallucinates less, but it doesn’t drastically change what you can do. In contrast, Claude 3.7 is seen as a surprisingly big upgrade on Claude’s side, especially for coding and reasoning tasks. On Hacker News, a user noted that Claude had “consistently been ahead for a year-ish” in some areas and with 3.7 it’s “back ahead again for my use cases”. The introduction of hybrid reasoning in one model impressed users, with some calling Claude 3.7 “frontier reasoning made practical” – it brought advanced chain-of-thought capabilities to everyday AI use.
Writing and “EQ”: Users widely praise GPT-4.5’s writing prowess. Ethan Mollick, a professor known for testing AI in education, said GPT-4.5 “can write beautifully, is very creative” but sometimes gets “oddly lazy on complex projects”. He humorously remarked that GPT-4.5 feels like Claude 3.7, while Claude 3.7 feels like GPT-4.5 – implying that GPT-4.5 adopted a bit of Claude’s conversational strength, and Claude 3.7 caught up to GPT’s level of sophistication. This suggests the gap in general writing and chatting has narrowed, with both models being excellent. GPT-4.5 might still have the edge in highly creative or empathetic writing (by design, OpenAI emphasized its “greater EQ” and testers sense it). One HN commenter said GPT-4.5’s writing “doesn't read like AI output anymore” – a strong compliment indicating it often chooses phrasing that sounds authentically human. Claude 3.7 also improved in avoiding the overly apologetic or canned phrases earlier AI might use. People appreciate Claude’s ability to maintain context over long conversations, which contributes to more coherent and relevant responses in extended dialogue (no repeating itself or forgetting, which can plague GPT if the context window is exceeded).
Coding and Problem Solving: On forums frequented by developers, Claude 3.7 generally gets higher marks for coding help. Hacker News users noted “Claude 3.7 Sonnet is better than o3-mini at coding… I’ll stick with Claude 3.7 for now for my open source projects”. They cite that Claude’s coding accuracy and its new Claude Code tool make it very practical for programming assistance. GPT-4.5, by contrast, received mixed feedback in this area: “so far its coding performance is bad, but its writing abilities are totally insane” said one HN user during the first day of testing.
Another pointed out that purely ability-oriented tasks like coding didn’t see big gains with GPT-4.5, whereas fact-based QA saw large improvements (thanks to GPT-4.5’s expanded training data). This aligns with official benchmarks: OpenAI’s own comparison showed GPT-4.5 still trailing a specialized reasoning model on coding benchmarks, even though it overtook GPT-4. Bottom line from many users: if you need an AI pair programmer, Claude is currently the favorite, but if you need a quick explanation or a small script with very natural language instructions, GPT-4.5 will do the job (just at higher cost).
Community Reactions to Pricing: There’s a clear consensus that GPT-4.5 is extremely expensive for what it offers. The phrase “GPT-4.5 pricing is insane” comes directly from a top comment on Hacker News, which then breaks down how much more it costs than GPT-4. Many feel that OpenAI’s strategy here is to charge a premium for the absolute best model, even if the improvements are incremental, targeting enterprise clients who are less price-sensitive.
Some cynically commented that OpenAI launched GPT-4.5 in reaction to Anthropic’s Claude 3.7 release, perhaps to maintain bragging rights or momentum in the AI race. On Reddit, users joked “OpenAI saw the Sonnet 3.7 launch and said ‘we have to do something NOW!’”. The close timing of the releases (Anthropic announced Claude 3.7 on Feb 24, 2025, OpenAI released GPT-4.5 on Feb 27, 2025 supports the idea that competition is fierce.
Meanwhile, Anthropic’s move to keep Claude’s pricing low drew positive remarks: “Doubly so with how good Claude 3.7 is at $3/1M tokens” (GPT-4.5 | Hacker News) – many developers are excited that they can afford to use a state-of-the-art model extensively without breaking the bank. Some have even suggested that Claude 3.7 (and other new entrants like xAI’s Grok-3) are putting pressure on OpenAI to either lower prices or innovate further, which is good for consumers in the long run.
Official Stances and Vision: OpenAI frames GPT-4.5 as a research preview – essentially acknowledging it’s an experiment. They explicitly said GPT-4.5 is “not a replacement for GPT-4” and they’re watching to see if it provides unique value before committing long-term. This unusual messaging (for a product release) made industry observers call GPT-4.5 a “very odd and interesting model”. It’s bigger and more compute-intensive without a clear revolutionary capability, leading some to speculate that OpenAI released it partly to showcase progress (10× more pretraining data than GPT-4) and partly to counter rivals. Anthropic, on the other hand, is very bullish on their approach with Claude 3.7. In their announcement they call it “our most intelligent model to date” and emphasize the philosophical difference of integrating reasoning into the main model rather than treating it as a separate process. Dario Amodei (Anthropic’s CEO) and team seem to suggest this is a path toward AI that can both think deeply and respond promptly in a single system. They also highlight real-world business uses: Claude 3.7 was optimized with less focus on academic puzzles and more on tasks “how businesses actually use LLMs”. This resonates with users who want practical help (e.g., writing code that actually runs, analyzing data, drafting content) rather than just theoretical benchmark wins.
Forum Discussions – Summary: In places like Reddit’s r/ChatGPT and r/ClaudeAI, you’ll find users experimenting with the same prompts on both models and sharing results. The consensus so far: GPT-4.5 gives slightly more articulate and contextually rich answers, and is particularly good at things like storytelling or nuanced writing. Claude 3.7 gives longer and more detailed answers when asked, and handles complex multi-part instructions gracefully (thanks to the extended mode). On tasks like summarizing a long article or documentation, Claude’s output is often more comprehensive because it can actually take in the whole text at once. On creative tasks, some still prefer GPT-4.5 – for instance, writing a witty poem or a heartfelt letter, GPT’s style might edge out Claude’s. On Q&A accuracy, GPT-4.5 has closed a lot of gaps; one metric (SimpleQA) showed GPT-4.5 jumping to ~62.5% accuracy vs ~47% for GPT-4, indicating fewer factual errors. Users have noticed this reduction in hallucination, saying GPT-4.5 is more trustworthy on factual queries. Claude was already strong at not hallucinating too much (Anthropic’s earlier Claude 3.5 was noted for truthful answers), and Claude 3.7 further reduces mistakes in domains like reading comprehension or logic.
In the end, many power users suggest using both models to complement each other. For example, one might use Claude 3.7 for brainstorming and outlining a complex project plan (leveraging its long context to include lots of background info), then use GPT-4.5 to polish the final written plan for tone and clarity. Or use GPT-4.5 to generate a draft, then ask Claude to critique and improve the reasoning or check for errors. The competition between OpenAI and Anthropic is clearly benefiting users, as each iteration forces the other to improve.
As one industry commentator put it, GPT-4.5 and Claude 3.7 have essentially swapped some strengths, and now it’s about personal preference and specific needs. OpenAI’s model might be the “friendlier” chat companion with a hefty price tag, while Anthropic’s is the “workhorse” that you can lean on for heavy-duty tasks at a lower cost.
Both GPT-4.5 and Claude 3.7 are top-tier AI assistants, and choosing between them depends on your priorities. Developers may lean towards Claude for its coding savvy and lower cost, while writers and communicators might favor GPT-4.5’s ultra-refined prose (if budget is no issue). Email-heavy professionals will appreciate either model’s help, but Claude’s memory and GPT-4.5’s flair are each unique. Pricing is a major differentiator – Claude 3.7 offers a high-value proposition, whereas GPT-4.5 asks you to pay a premium for incremental gains. General user opinion tilts in Claude’s favor for practical tasks and in GPT-4.5’s favor for sheer conversational quality. The good news is that both are improving rapidly, and having two strong competitors means users have options. As the discussions on forums show, this head-to-head is driving lots of excitement – and a bit of debate – but ultimately it’s pushing AI technology forward in a way where different strengths cater to different needs.
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