Mistral Medium 3.5 vs Qwen3 VL 235B A22B Thinking
| Signal | Mistral Medium 3.5 | Delta | Qwen3 VL 235B A22B Thinking |
|---|---|---|---|
Capabilities | 83 | -- | |
Benchmarks | 70 | +4 | |
Pricing | 93 | -3 | |
Context window size | 86 | +5 | |
Recency | 100 | +25 | |
Output Capacity | 20 | -55 | |
| Overall Result | 3 wins | of 6 | 2 wins |
Score History
71.7
current score
Mistral Medium 3.5
right now
69.4
current score
Mistral Medium 3.5
Mistral AI
Qwen3 VL 235B A22B Thinking
Alibaba
Qwen3 VL 235B A22B Thinking saves you $285.00/month
That's $3420.00/year compared to Mistral Medium 3.5 at your current usage level of 100K calls/month.
| Metric | Mistral Medium 3.5 | Qwen3 VL 235B A22B Thinking | Winner |
|---|---|---|---|
| Overall Score | 72 | 69 | Mistral Medium 3.5 |
| Rank | #153 | #164 | Mistral Medium 3.5 |
| Quality Rank | #153 | #164 | Mistral Medium 3.5 |
| Adoption Rank | #153 | #164 | Mistral Medium 3.5 |
| Parameters | -- | 235B | -- |
| Context Window | 262K | 131K | Mistral Medium 3.5 |
| Pricing | $1.50/$7.50/M | $0.40/$4.00/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 83 | Mistral Medium 3.5 |
| Benchmarks | 70 | 66 | Mistral Medium 3.5 |
| Pricing | 93 | 96 | Qwen3 VL 235B A22B Thinking |
| Context window size | 86 | 81 | Mistral Medium 3.5 |
| Recency | 100 | 75 | Mistral Medium 3.5 |
| Output Capacity | 20 | 75 | Qwen3 VL 235B A22B Thinking |
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 72/100 (rank #153), placing it in the top 48% of all 290 models tracked.
Scores 69/100 (rank #164), placing it in the top 44% of all 290 models tracked.
With only a 2-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.
Choose Mistral Medium 3.5 when you need:
- Processing long documents or large codebases (262K token context)
- Step-by-step reasoning and chain-of-thought problem solving
Choose Qwen3 VL 235B A22B Thinking when you need:
- High-volume production workloads where API costs must be minimized
- Step-by-step reasoning and chain-of-thought problem solving
- Self-hosted deployments where you need full control over the model
Qwen3 VL 235B A22B Thinking offers 51% better value per quality point. At 1M tokens/day, you'd spend $66.00/month with Qwen3 VL 235B A22B Thinking vs $135.00/month with Mistral Medium 3.5 - a $69.00 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
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 VL 235B A22B Thinking 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 ($4.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (72/100) 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 VL 235B A22B Thinking are extremely close in overall performance (only 2.299999999999997 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
By Use Case
Best for Quality
Mistral Medium 3.5
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 VL 235B A22B Thinking
51% 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
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Reliability - Higher uptime and faster response speeds
- Choose for Prototyping - Stronger community support and better developer experience
- Choose for Production - Wider enterprise adoption and proven at scale
| Capability | Mistral Medium 3.5 | Qwen3 VL 235B A22B Thinking |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Mistral Medium 3.5
Mistral AI
Qwen3 VL 235B A22B Thinking
Alibaba
Qwen3 VL 235B A22B Thinking saves you $6.18/month
That's 53% 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 VL 235B A22B Thinking |
|---|---|---|
| Context Window | 262K | 131K |
| Max Output Tokens | -- | 32,768 |
| Open Source | No | Yes |
| Created | Apr 30, 2026 | Sep 23, 2025 |