| Signal | Claude Opus 4.1 | Delta | Mistral Large |
|---|---|---|---|
Capabilities | 100 | +50 | |
Benchmarks | 73 | -2 | |
Pricing | 75 | +69 | |
Context window size | 84 | +3 | |
Recency | 89 | +89 | |
Output Capacity | 75 | +55 | |
| Overall Result | 5 wins | of 6 | 1 wins |
11
days higher
8
days
11
days higher
Anthropic
Mistral AI
Mistral Large saves you $4750.00/month
That's $57000.00/year compared to Claude Opus 4.1 at your current usage level of 100K calls/month.
| Metric | Claude Opus 4.1 | Mistral Large | Winner |
|---|---|---|---|
| Overall Score | 75 | 74 | Claude Opus 4.1 |
| Rank | #45 | #47 | Claude Opus 4.1 |
| Quality Rank | #45 | #47 | Claude Opus 4.1 |
| Adoption Rank | #45 | #47 | Claude Opus 4.1 |
| Parameters | -- | -- | -- |
| Context Window | 200K | 128K | Claude Opus 4.1 |
| Pricing | $15.00/$75.00/M | $2.00/$6.00/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | Claude Opus 4.1 |
| Benchmarks | 73 | 75 | Mistral Large |
| Pricing | 75 | 6 | Claude Opus 4.1 |
| Context window size | 84 | 81 | Claude Opus 4.1 |
| Recency | 89 | 0 | Claude Opus 4.1 |
| Output Capacity | 75 | 20 | Claude Opus 4.1 |
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%). Here's what the scores mean for these two models:
Scores 75/100 (rank #45), placing it in the top 85% of all 290 models tracked.
Scores 74/100 (rank #47), placing it in the top 84% of all 290 models tracked.
With only a 1-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 91% better value per quality point. At 1M tokens/day, you'd spend $120.00/month with Mistral Large vs $1350.00/month with Claude Opus 4.1 - a $1230.00 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 (75/100) 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 Opus 4.1 and Mistral Large are extremely close in overall performance (only 1.0999999999999943 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Claude Opus 4.1
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Large
91% lower pricing; better value at scale
Best for Reliability
Claude Opus 4.1
Higher uptime and faster response speeds
Best for Prototyping
Claude Opus 4.1
Stronger community support and better developer experience
Best for Production
Claude Opus 4.1
Wider enterprise adoption and proven at scale
by Anthropic
| Capability | Claude Opus 4.1 | Mistral Large |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
Anthropic
Mistral AI
Mistral Large saves you $106.20/month
That's 91% cheaper than Claude Opus 4.1 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 Opus 4.1 | Mistral Large |
|---|---|---|
| Context Window | 200K | 128K |
| Max Output Tokens | 32,000 | -- |
| Open Source | No | No |
| Created | Aug 5, 2025 | Feb 26, 2024 |
Claude Opus 4.1 scores 75/100 (rank #45) compared to Mistral Large's 74/100 (rank #47), giving it a 1-point advantage. Claude Opus 4.1 is the stronger overall choice, though Mistral Large may excel in specific areas like cost efficiency.
Claude Opus 4.1 is ranked #45 and Mistral Large is ranked #47 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 Opus 4.1's $75.00/M output tokens - 12.5x more expensive. Input token pricing: Claude Opus 4.1 at $15.00/M vs Mistral Large at $2.00/M.
Claude Opus 4.1 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.