| Signal | Devstral 2 2512 | Delta | Qwen3 4B (free) |
|---|---|---|---|
Capabilities | 50 | -17 | |
Pricing | 2 | -28 | |
Context window size | 86 | +13 | |
Recency | 100 | +25 | |
Output Capacity | 20 | -- | |
| Overall Result | 2 wins | of 5 | 2 wins |
11
days ranked higher
4
days
15
days ranked higher
Mistral AI
Alibaba
Qwen3 4B (free) saves you $140.00/month
That's $1680.00/year compared to Devstral 2 2512 at your current usage level of 100K calls/month.
| Metric | Devstral 2 2512 | Qwen3 4B (free) | Winner |
|---|---|---|---|
| Overall Score | 63 | 63 | Devstral 2 2512 |
| Rank | #175 | #176 | Devstral 2 2512 |
| Quality Rank | #175 | #176 | Devstral 2 2512 |
| Adoption Rank | #175 | #176 | Devstral 2 2512 |
| Parameters | -- | 4B | -- |
| Context Window | 262K | 41K | Devstral 2 2512 |
| Pricing | $0.40/$2.00/M | Free | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | Qwen3 4B (free) |
| Pricing | 2 | 30 | Qwen3 4B (free) |
| Context window size | 86 | 73 | Devstral 2 2512 |
| Recency | 100 | 75 | Devstral 2 2512 |
| Output Capacity | 20 | 20 | Devstral 2 2512 |
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 63/100 (rank #175), placing it in the top 40% of all 290 models tracked.
Scores 63/100 (rank #176), placing it in the top 40% 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.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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. Qwen3 4B (free) 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 ($0.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (63/100) correlates with better nuance, coherence, and style in long-form content
Devstral 2 2512 and Qwen3 4B (free) are extremely close in overall performance (only 0.10000000000000142 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
Qwen3 4B (free)
100% 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 | Qwen3 4B (free) |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Mistral AI
Alibaba
Qwen3 4B (free) saves you $3.12/month
That's 100% cheaper than Devstral 2 2512 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 | Qwen3 4B (free) |
|---|---|---|
| Context Window | 262K | 41K |
| Max Output Tokens | -- | -- |
| Open Source | Yes | Yes |
| Created | Dec 9, 2025 | Apr 30, 2025 |
Devstral 2 2512 scores 63/100 (rank #175) compared to Qwen3 4B (free)'s 63/100 (rank #176), giving it a 0-point advantage. Devstral 2 2512 is the stronger overall choice, though Qwen3 4B (free) may excel in specific areas like cost efficiency.
Devstral 2 2512 is ranked #175 and Qwen3 4B (free) is ranked #176 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.
Qwen3 4B (free) is cheaper at $0.00/M output tokens vs Devstral 2 2512's $2.00/M output tokens — 2000.0x more expensive. Input token pricing: Devstral 2 2512 at $0.40/M vs Qwen3 4B (free) at $0.00/M.
Devstral 2 2512 has a larger context window of 262,144 tokens compared to Qwen3 4B (free)'s 40,960 tokens. A larger context window means the model can process longer documents and conversations.