| Signal | Mistral Medium 3.5 | Delta | Qwen3.6 27B |
|---|---|---|---|
Capabilities | 83 | -- | |
Pricing | 93 | -4 | |
Context window size | 86 | -- | |
Recency | 100 | -- | |
Output Capacity | 20 | -62 | |
| Overall Result | 0 wins | of 5 | 2 wins |
Score History
40
current score
Tied
right now
40
current score
Mistral AI
Alibaba
Qwen3.6 27B saves you $333.00/month
That's $3996.00/year compared to Mistral Medium 3.5 at your current usage level of 100K calls/month.
| Metric | Mistral Medium 3.5 | Qwen3.6 27B | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #187 | #201 | Mistral Medium 3.5 |
| Quality Rank | #187 | #201 | Mistral Medium 3.5 |
| Adoption Rank | #187 | #201 | Mistral Medium 3.5 |
| Parameters | -- | 27B | -- |
| Context Window | 262K | 262K | -- |
| Pricing | $1.50/$7.50/M | $0.32/$3.20/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 83 | Mistral Medium 3.5 |
| Pricing | 93 | 97 | Qwen3.6 27B |
| Context window size | 86 | 86 | Mistral Medium 3.5 |
| Recency | 100 | 100 | Mistral Medium 3.5 |
| Output Capacity | 20 | 82 | Qwen3.6 27B |
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 40/100 (rank #187), placing it in the top 36% of all 290 models tracked.
Scores 40/100 (rank #201), placing it in the top 31% 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.
Qwen3.6 27B offers 61% better value per quality point. At 1M tokens/day, you'd spend $52.80/month with Qwen3.6 27B vs $135.00/month with Mistral Medium 3.5 - a $82.20 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
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Qwen3.6 27B 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 ($3.20/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
Mistral Medium 3.5 and Qwen3.6 27B 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
Mistral Medium 3.5
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.6 27B
61% lower pricing; better value at scale
Best for Reliability
Mistral Medium 3.5
Higher uptime and faster response speeds
Best for Prototyping
Mistral Medium 3.5
Stronger community support and better developer experience
Best for Production
Mistral Medium 3.5
Wider enterprise adoption and proven at scale
by Mistral AI
| Capability | Mistral Medium 3.5 | Qwen3.6 27B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Mistral AI
Alibaba
Qwen3.6 27B saves you $7.28/month
That's 62% cheaper than Mistral Medium 3.5 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 | Mistral Medium 3.5 | Qwen3.6 27B |
|---|---|---|
| Context Window | 262K | 262K |
| Max Output Tokens | -- | 81,920 |
| Open Source | No | Yes |
| Created | Apr 30, 2026 | Apr 27, 2026 |