Model Comparison
Pixtral Large
vs. Qwen3.6 27B (Non-reasoning)
Comparing 2 AI models · 12 benchmarks · Mistral, Alibaba
Recommended Pick
AlQwen3.6 27B (Non-reasoning)13 metric winsStrongest on: Value, Input price, Output price
Best Value
Qwen3.6 27B (Non-reasoning)
100.0 value score
42.3 reasoning / $1.35/1M
Lowest Price
Qwen3.6 27B (Non-reasoning)
$0.60/1M input price
Best Reasoning
Qwen3.6 27B (Non-reasoning)
42.3 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3.6 27B (Non-reasoning)
46.6 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Best value
Qwen3.6 27B (Non-reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Qwen3.6 27B (Non-reasoning) is 3.3x cheaper on input tokens than Pixtral Large.
Reasoning gap
Qwen3.6 27B (Non-reasoning) leads Pixtral Large by 21.6 points on reasoning.
Top-pick rationale
Qwen3.6 27B (Non-reasoning) wins 13 measurable categories, including Value, Input price, Output price, Blended price.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Pixtral Large
Mistral
TTFT
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Time
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tok/s
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Tokens
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Cost
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Qwen3.6 27B (Non-reasoning)
Alibaba
TTFT
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Time
—
tok/s
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Tokens
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Cost
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Which answer was more useful?
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Full Comparison
| Metric | Mi Pixtral Large | Top Pick Al Qwen3.6 27B (Non-reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $2.00/1M | $0.60/1M |
| Output Cost | $6.00/1M | $3.60/1M |
| Blended (3:1) | $3.00/1M | $1.35/1M |
| Specifications | ||
| Organization | Mistral | Alibaba |
| Release Date | Nov 18, 2024 | Apr 22, 2026 |
| Performance & Speed | ||
| Throughput | — | 59.8 tok/s |
| TTFT | — | 1571ms |
| Latency | — | 1571ms |
| Composite Indices | ||
| Value Score | 22.1 | 100.0 |
| Reasoning Score | 20.7 | 42.3 |
| Intelligence | 8.1 | 30.5 |
| Coding | — | 46.6 |
| Math | 2.3 | — |
| Standard Benchmarks | ||
| GPQA | 50.5% | 82.9% |
| MMLU Pro | 70.1% | — |
| HLE | 3.6% | 13.6% |
| LiveCodeBench | 26.1% | — |
| MATH 500 | 71.4% | — |
| AIME 2025 | 2.3% | — |
| AIME (Original) | 7.0% | — |
| SciCode | 29.2% | 37.3% |
| LCR | 10.3% | 55.0% |
| IFBench | 34.5% | 45.7% |
| TAU-bench v2 | 36.5% | 93.6% |
| TerminalBench Hard | — | 21.2% |
Key Takeaways
Qwen3.6 27B (Non-reasoning) offers the best value at $0.60/1M,making it ideal for high-volume applications and cost-conscious projects.
Qwen3.6 27B (Non-reasoning) has the strongest reasoning profile with a 42.3 reasoning score,combining the available reasoning-heavy benchmarks.
Qwen3.6 27B (Non-reasoning) reaches a 46.6 coding index,making it the top choice for software development and code generation tasks.
All models support context windows of ∞+ tokens,suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
Pixtral Large
- General-purpose AI
- Versatile applications
Qwen3.6 27B (Non-reasoning)
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
