| Signal | GPT-5.1-Codex-Max | Delta | Devstral 2 2512 |
|---|---|---|---|
Capabilities | 100 | +50 | |
Pricing | 10 | +8 | |
Context window size | 89 | +3 | |
Recency | 100 | -- | |
Output Capacity | 85 | +65 | |
| Overall Result | 4 wins | of 5 | 0 wins |
7
days higher
4
days
19
days higher
OpenAI
Mistral AI
Devstral 2 2512 saves you $485.00/month
That's $5820.00/year compared to GPT-5.1-Codex-Max at your current usage level of 100K calls/month.
| Metric | GPT-5.1-Codex-Max | Devstral 2 2512 | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #165 | #163 | Devstral 2 2512 |
| Quality Rank | #165 | #163 | Devstral 2 2512 |
| Adoption Rank | #165 | #163 | Devstral 2 2512 |
| Parameters | -- | -- | -- |
| Context Window | 400K | 262K | GPT-5.1-Codex-Max |
| Pricing | $1.25/$10.00/M | $0.40/$2.00/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | GPT-5.1-Codex-Max |
| Pricing | 10 | 2 | GPT-5.1-Codex-Max |
| Context window size | 89 | 86 | GPT-5.1-Codex-Max |
| Recency | 100 | 100 | GPT-5.1-Codex-Max |
| Output Capacity | 85 | 20 | GPT-5.1-Codex-Max |
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 40/100 (rank #165), placing it in the top 43% of all 290 models tracked.
Scores 40/100 (rank #163), placing it in the top 44% 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.
Devstral 2 2512 offers 79% better value per quality point. At 1M tokens/day, you'd spend $36.00/month with Devstral 2 2512 vs $168.75/month with GPT-5.1-Codex-Max - a $132.75 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. Devstral 2 2512 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($2.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) 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
GPT-5.1-Codex-Max and Devstral 2 2512 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
GPT-5.1-Codex-Max
Marginally better benchmark scores; both are excellent
Best for Cost
Devstral 2 2512
79% lower pricing; better value at scale
Best for Reliability
GPT-5.1-Codex-Max
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.1-Codex-Max
Stronger community support and better developer experience
Best for Production
GPT-5.1-Codex-Max
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.1-Codex-Max | Devstral 2 2512 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Mistral AI
Devstral 2 2512 saves you $11.13/month
That's 78% cheaper than GPT-5.1-Codex-Max 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 | GPT-5.1-Codex-Max | Devstral 2 2512 |
|---|---|---|
| Context Window | 400K | 262K |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | Yes |
| Created | Dec 4, 2025 | Dec 9, 2025 |
Both GPT-5.1-Codex-Max and Devstral 2 2512 score 40/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
GPT-5.1-Codex-Max is ranked #165 and Devstral 2 2512 is ranked #163 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.
Devstral 2 2512 is cheaper at $2.00/M output tokens vs GPT-5.1-Codex-Max's $10.00/M output tokens - 5.0x more expensive. Input token pricing: GPT-5.1-Codex-Max at $1.25/M vs Devstral 2 2512 at $0.40/M.
GPT-5.1-Codex-Max has a larger context window of 400,000 tokens compared to Devstral 2 2512's 262,144 tokens. A larger context window means the model can process longer documents and conversations.