| Signal | GPT-5 Nano | Delta | Devstral Small 1.1 |
|---|---|---|---|
Capabilities | 100 | +50 | |
Benchmarks | 48 | +3 | |
Pricing | 100 | 0 | |
Context window size | 89 | +8 | |
Recency | 89 | +5 | |
Output Capacity | 85 | +65 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
46.9
current score
Devstral Small 1.1
right now
47.2
current score
OpenAI
Mistral AI
| Metric | GPT-5 Nano | Devstral Small 1.1 | Winner |
|---|---|---|---|
| Overall Score | 47 | 47 | Devstral Small 1.1 |
| Rank | #157 | #156 | Devstral Small 1.1 |
| Quality Rank | #157 | #156 | Devstral Small 1.1 |
| Adoption Rank | #157 | #156 | Devstral Small 1.1 |
| Parameters | -- | -- | -- |
| Context Window | 400K | 131K | GPT-5 Nano |
| Pricing | $0.05/$0.40/M | $0.10/$0.30/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | GPT-5 Nano |
| Benchmarks | 48 | 45 | GPT-5 Nano |
| Pricing | 100 | 100 | Devstral Small 1.1 |
| Context window size | 89 | 81 | GPT-5 Nano |
| Recency | 89 | 84 | GPT-5 Nano |
| Output Capacity | 85 | 20 | GPT-5 Nano |
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 47/100 (rank #157), placing it in the top 46% of all 290 models tracked.
Scores 47/100 (rank #156), placing it in the top 47% 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 Small 1.1 offers 11% better value per quality point. At 1M tokens/day, you'd spend $6.00/month with Devstral Small 1.1 vs $6.75/month with GPT-5 Nano - a $0.75 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 Small 1.1 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 ($0.30/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (47/100) 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 Nano and Devstral Small 1.1 are extremely close in overall performance (only 0.30000000000000426 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-5 Nano
Marginally better benchmark scores; both are excellent
Best for Cost
Devstral Small 1.1
11% lower pricing; better value at scale
Best for Reliability
GPT-5 Nano
Higher uptime and faster response speeds
Best for Prototyping
GPT-5 Nano
Stronger community support and better developer experience
Best for Production
GPT-5 Nano
Wider enterprise adoption and proven at scale
by OpenAI
by Mistral AI
| Capability | GPT-5 Nano | Devstral Small 1.1 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Mistral AI
Devstral Small 1.1 saves you $0.0300/month
That's 5% cheaper than GPT-5 Nano 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 Nano | Devstral Small 1.1 |
|---|---|---|
| Context Window | 400K | 131K |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | Yes |
| Created | Aug 7, 2025 | Jul 10, 2025 |
Devstral Small 1.1 scores 47/100 (rank #156) compared to GPT-5 Nano's 47/100 (rank #157), giving it a 0-point advantage. Devstral Small 1.1 is the stronger overall choice, though GPT-5 Nano may excel in specific areas like certain benchmarks.
GPT-5 Nano is ranked #157 and Devstral Small 1.1 is ranked #156 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 Small 1.1 is cheaper at $0.30/M output tokens vs GPT-5 Nano's $0.40/M output tokens - 1.3x more expensive. Input token pricing: GPT-5 Nano at $0.05/M vs Devstral Small 1.1 at $0.10/M.
GPT-5 Nano has a larger context window of 400,000 tokens compared to Devstral Small 1.1's 131,072 tokens. A larger context window means the model can process longer documents and conversations.