| Signal | Devstral 2 2512 | Delta | Qwen VL Max |
|---|---|---|---|
Capabilities | 50 | -17 | |
Pricing | 2 | 0 | |
Context window size | 86 | +5 | |
Recency | 100 | +43 | |
Output Capacity | 20 | -55 | |
| Overall Result | 2 wins | of 5 | 3 wins |
6
days ranked higher
4
days
20
days ranked higher
Mistral AI
Alibaba
Devstral 2 2512 saves you $16.00/month
That's $192.00/year compared to Qwen VL Max at your current usage level of 100K calls/month.
| Metric | Devstral 2 2512 | Qwen VL Max | Winner |
|---|---|---|---|
| Overall Score | 68 | 68 | Qwen VL Max |
| Rank | #169 | #167 | Qwen VL Max |
| Quality Rank | #169 | #167 | Qwen VL Max |
| Adoption Rank | #169 | #167 | Qwen VL Max |
| Parameters | -- | -- | -- |
| Context Window | 262K | 131K | Devstral 2 2512 |
| Pricing | $0.40/$2.00/M | $0.52/$2.08/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | Qwen VL Max |
| Pricing | 2 | 2 | Qwen VL Max |
| Context window size | 86 | 81 | Devstral 2 2512 |
| Recency | 100 | 57 | Devstral 2 2512 |
| Output Capacity | 20 | 75 | Qwen VL 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 68/100 (rank #169), placing it in the top 42% of all 290 models tracked.
Scores 68/100 (rank #167), placing it in the top 43% 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 8% better value per quality point. At 1M tokens/day, you'd spend $36.00/month with Devstral 2 2512 vs $39.00/month with Qwen VL Max - a $3.00 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 2 2512 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (262K 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 (68/100) 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
Devstral 2 2512 and Qwen VL Max are extremely close in overall performance (only 0.3999999999999915 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Devstral 2 2512
Marginally better benchmark scores; both are excellent
Best for Cost
Devstral 2 2512
8% lower pricing; better value at scale
Best for Reliability
Devstral 2 2512
Higher uptime and faster response speeds
Best for Prototyping
Devstral 2 2512
Stronger community support and better developer experience
Best for Production
Devstral 2 2512
Wider enterprise adoption and proven at scale
by Mistral AI
| Capability | Devstral 2 2512 | Qwen VL Max |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Mistral AI
Alibaba
Devstral 2 2512 saves you $0.3120/month
That's 9% cheaper than Qwen VL 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 2 2512 | Qwen VL Max |
|---|---|---|
| Context Window | 262K | 131K |
| Max Output Tokens | -- | 32,768 |
| Open Source | Yes | No |
| Created | Dec 9, 2025 | Feb 1, 2025 |
Qwen VL Max scores 68/100 (rank #167) compared to Devstral 2 2512's 68/100 (rank #169), giving it a 0-point advantage. Qwen VL Max is the stronger overall choice, though Devstral 2 2512 may excel in specific areas like cost efficiency.
Devstral 2 2512 is ranked #169 and Qwen VL Max is ranked #167 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 2 2512 is cheaper at $2.00/M output tokens vs Qwen VL Max's $2.08/M output tokens - 1.0x more expensive. Input token pricing: Devstral 2 2512 at $0.40/M vs Qwen VL Max at $0.52/M.
Devstral 2 2512 has a larger context window of 262,144 tokens compared to Qwen VL Max's 131,072 tokens. A larger context window means the model can process longer documents and conversations.