| Signal | Claude 3.7 Sonnet | Delta | Codestral 2508 |
|---|---|---|---|
Capabilities | 83 | +33 | |
Benchmarks | 83 | +83 | |
Pricing | 15 | +14 | |
Context window size | 84 | -2 | |
Recency | 63 | -29 | |
Output Capacity | 80 | +60 | |
| Overall Result | 4 wins | of 6 | 2 wins |
30
days ranked higher
0
days
0
days ranked higher
Anthropic
Mistral AI
Codestral 2508 saves you $975.00/month
That's $11700.00/year compared to Claude 3.7 Sonnet at your current usage level of 100K calls/month.
| Metric | Claude 3.7 Sonnet | Codestral 2508 | Winner |
|---|---|---|---|
| Overall Score | 79 | 61 | Claude 3.7 Sonnet |
| Rank | #80 | #193 | Claude 3.7 Sonnet |
| Quality Rank | #80 | #193 | Claude 3.7 Sonnet |
| Adoption Rank | #80 | #193 | Claude 3.7 Sonnet |
| Parameters | -- | -- | -- |
| Context Window | 200K | 256K | Codestral 2508 |
| Pricing | $3.00/$15.00/M | $0.30/$0.90/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 50 | Claude 3.7 Sonnet |
| Benchmarks | 83 | -- | Claude 3.7 Sonnet |
| Pricing | 15 | 1 | Claude 3.7 Sonnet |
| Context window size | 84 | 86 | Codestral 2508 |
| Recency | 63 | 92 | Codestral 2508 |
| Output Capacity | 80 | 20 | Claude 3.7 Sonnet |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 79/100 (rank #80), placing it in the top 73% of all 290 models tracked.
Scores 61/100 (rank #193), placing it in the top 34% of all 290 models tracked.
Claude 3.7 Sonnet has a 18-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Codestral 2508 offers 93% better value per quality point. At 1M tokens/day, you'd spend $18.00/month with Codestral 2508 vs $270.00/month with Claude 3.7 Sonnet — a $252.00 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. Codestral 2508 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (256K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.90/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (79/100) 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 clearly outperforms Codestral 2508 with a significant 17.799999999999997-point lead. For most general use cases, Claude 3.7 Sonnet is the stronger choice. However, Codestral 2508 may still excel in niche scenarios.
Best for Quality
Claude 3.7 Sonnet
Marginally better benchmark scores; both are excellent
Best for Cost
Codestral 2508
93% lower pricing; better value at scale
Best for Reliability
Claude 3.7 Sonnet
Higher uptime and faster response speeds
Best for Prototyping
Claude 3.7 Sonnet
Stronger community support and better developer experience
Best for Production
Claude 3.7 Sonnet
Wider enterprise adoption and proven at scale
by Anthropic
| Capability | Claude 3.7 Sonnet | Codestral 2508 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
Anthropic
Mistral AI
Codestral 2508 saves you $21.78/month
That's 93% cheaper than Claude 3.7 Sonnet 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 | Codestral 2508 |
|---|---|---|
| Context Window | 200K | 256K |
| Max Output Tokens | 64,000 | -- |
| Open Source | No | No |
| Created | Feb 24, 2025 | Aug 1, 2025 |
Claude 3.7 Sonnet scores 79/100 (rank #80) compared to Codestral 2508's 61/100 (rank #193), giving it a 18-point advantage. Claude 3.7 Sonnet is the stronger overall choice, though Codestral 2508 may excel in specific areas like cost efficiency.
Claude 3.7 Sonnet is ranked #80 and Codestral 2508 is ranked #193 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Codestral 2508 is cheaper at $0.90/M output tokens vs Claude 3.7 Sonnet's $15.00/M output tokens — 16.7x more expensive. Input token pricing: Claude 3.7 Sonnet at $3.00/M vs Codestral 2508 at $0.30/M.
Codestral 2508 has a larger context window of 256,000 tokens compared to Claude 3.7 Sonnet's 200,000 tokens. A larger context window means the model can process longer documents and conversations.