| Signal | Devstral Small 1.1 | Delta | Qwen-Max |
|---|---|---|---|
Capabilities | 50 | -- | |
Pricing | 0 | -4 | |
Context window size | 81 | +10 | |
Recency | 88 | +29 | |
Output Capacity | 20 | -45 | |
| Overall Result | 2 wins | of 5 | 2 wins |
12
days ranked higher
5
days
13
days ranked higher
Mistral AI
Alibaba
Devstral Small 1.1 saves you $287.00/month
That's $3444.00/year compared to Qwen-Max at your current usage level of 100K calls/month.
| Metric | Devstral Small 1.1 | Qwen-Max | Winner |
|---|---|---|---|
| Overall Score | 59 | 58 | Devstral Small 1.1 |
| Rank | #211 | #218 | Devstral Small 1.1 |
| Quality Rank | #211 | #218 | Devstral Small 1.1 |
| Adoption Rank | #211 | #218 | Devstral Small 1.1 |
| Parameters | -- | -- | -- |
| Context Window | 131K | 33K | Devstral Small 1.1 |
| Pricing | $0.10/$0.30/M | $1.04/$4.16/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | Devstral Small 1.1 |
| Pricing | 0 | 4 | Qwen-Max |
| Context window size | 81 | 72 | Devstral Small 1.1 |
| Recency | 88 | 59 | Devstral Small 1.1 |
| Output Capacity | 20 | 65 | Qwen-Max |
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 59/100 (rank #211), placing it in the top 28% of all 290 models tracked.
Scores 58/100 (rank #218), placing it in the top 25% 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.
Devstral Small 1.1 offers 92% better value per quality point. At 1M tokens/day, you'd spend $6.00/month with Devstral Small 1.1 vs $78.00/month with Qwen-Max — a $72.00 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. Devstral Small 1.1 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K 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 (59/100) correlates with better nuance, coherence, and style in long-form content
Devstral Small 1.1 and Qwen-Max are extremely close in overall performance (only 1 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Devstral Small 1.1
Marginally better benchmark scores; both are excellent
Best for Cost
Devstral Small 1.1
92% lower pricing; better value at scale
Best for Reliability
Devstral Small 1.1
Higher uptime and faster response speeds
Best for Prototyping
Devstral Small 1.1
Stronger community support and better developer experience
Best for Production
Devstral Small 1.1
Wider enterprise adoption and proven at scale
by Mistral AI
| Capability | Devstral Small 1.1 | Qwen-Max |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Mistral AI
Alibaba
Devstral Small 1.1 saves you $6.32/month
That's 92% cheaper than Qwen-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 | Devstral Small 1.1 | Qwen-Max |
|---|---|---|
| Context Window | 131K | 33K |
| Max Output Tokens | -- | 8,192 |
| Open Source | Yes | No |
| Created | Jul 10, 2025 | Feb 1, 2025 |
Devstral Small 1.1 scores 59/100 (rank #211) compared to Qwen-Max 's 58/100 (rank #218), giving it a 1-point advantage. Devstral Small 1.1 is the stronger overall choice, though Qwen-Max may excel in specific areas like certain benchmarks.
Devstral Small 1.1 is ranked #211 and Qwen-Max is ranked #218 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.
Devstral Small 1.1 is cheaper at $0.30/M output tokens vs Qwen-Max 's $4.16/M output tokens — 13.9x more expensive. Input token pricing: Devstral Small 1.1 at $0.10/M vs Qwen-Max at $1.04/M.
Devstral Small 1.1 has a larger context window of 131,072 tokens compared to Qwen-Max 's 32,768 tokens. A larger context window means the model can process longer documents and conversations.