| Signal | Claude 3.7 Sonnet (thinking) | Delta | Mistral Large |
|---|---|---|---|
Capabilities | 83 | +33 | |
Benchmarks | 65 | -4 | |
Pricing | 85 | -9 | |
Context window size | 84 | +3 | |
Recency | 59 | +59 | |
Output Capacity | 80 | +60 | |
| Overall Result | 4 wins | of 6 | 2 wins |
Score History
66.7
current score
Tied
right now
66.7
current score
Anthropic
Mistral AI
Mistral Large saves you $550.00/month
That's $6600.00/year compared to Claude 3.7 Sonnet (thinking) at your current usage level of 100K calls/month.
| Metric | Claude 3.7 Sonnet (thinking) | Mistral Large | Winner |
|---|---|---|---|
| Overall Score | 67 | 67 | -- |
| Rank | #76 | #77 | Claude 3.7 Sonnet (thinking) |
| Quality Rank | #76 | #77 | Claude 3.7 Sonnet (thinking) |
| Adoption Rank | #76 | #77 | Claude 3.7 Sonnet (thinking) |
| Parameters | -- | -- | -- |
| Context Window | 200K | 128K | Claude 3.7 Sonnet (thinking) |
| Pricing | $3.00/$15.00/M | $2.00/$6.00/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 50 | Claude 3.7 Sonnet (thinking) |
| Benchmarks | 65 | 69 | Mistral Large |
| Pricing | 85 | 94 | Mistral Large |
| Context window size | 84 | 81 | Claude 3.7 Sonnet (thinking) |
| Recency | 59 | 0 | Claude 3.7 Sonnet (thinking) |
| Output Capacity | 80 | 20 | Claude 3.7 Sonnet (thinking) |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 67/100 (rank #76), placing it in the top 74% of all 290 models tracked.
Scores 67/100 (rank #77), placing it in the top 74% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Mistral Large offers 56% better value per quality point. At 1M tokens/day, you'd spend $120.00/month with Mistral Large vs $270.00/month with Claude 3.7 Sonnet (thinking) - a $150.00 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Mistral Large also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (200K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($6.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (67/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Claude 3.7 Sonnet (thinking) and Mistral Large are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Claude 3.7 Sonnet (thinking)
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Large
56% lower pricing; better value at scale
Best for Reliability
Claude 3.7 Sonnet (thinking)
Higher uptime and faster response speeds
Best for Prototyping
Claude 3.7 Sonnet (thinking)
Stronger community support and better developer experience
Best for Production
Claude 3.7 Sonnet (thinking)
Wider enterprise adoption and proven at scale
by Anthropic
| Capability | Claude 3.7 Sonnet (thinking) | Mistral Large |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
Anthropic
Mistral AI
Mistral Large saves you $12.60/month
That's 54% cheaper than Claude 3.7 Sonnet (thinking) at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Claude 3.7 Sonnet (thinking) | Mistral Large |
|---|---|---|
| Context Window | 200K | 128K |
| Max Output Tokens | 64,000 | -- |
| Open Source | No | No |
| Created | Feb 24, 2025 | Feb 26, 2024 |
Both Claude 3.7 Sonnet (thinking) and Mistral Large score 67/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Claude 3.7 Sonnet (thinking) is ranked #76 and Mistral Large is ranked #77 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Mistral Large is cheaper at $6.00/M output tokens vs Claude 3.7 Sonnet (thinking)'s $15.00/M output tokens - 2.5x more expensive. Input token pricing: Claude 3.7 Sonnet (thinking) at $3.00/M vs Mistral Large at $2.00/M.
Claude 3.7 Sonnet (thinking) has a larger context window of 200,000 tokens compared to Mistral Large's 128,000 tokens. A larger context window means the model can process longer documents and conversations.