Model Comparison
Pixtral Large
vs. Qwen2.5 Max
Comparing 2 AI models · 11 benchmarks · Mistral, Alibaba
Recommended Pick
Strongest on: Input price, Output price, Reasoning
Lowest Price
Qwen2.5 Max
$0.00/1M input price
Best Reasoning
Qwen2.5 Max
36.0 reasoning score
Blends available reasoning benchmarks
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Price gap
Qwen2.5 Max is ∞x cheaper on input tokens than Pixtral Large.
Reasoning gap
Qwen2.5 Max leads Pixtral Large by 15.3 points on reasoning.
Top-pick rationale
Qwen2.5 Max wins 11 measurable categories, including Input price, Output price, Reasoning, Intelligence.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Pixtral Large
Mistral
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Qwen2.5 Max
Alibaba
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
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Full Comparison
| Metric | Mi Pixtral Large | Top Pick Al Qwen2.5 Max |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $2.00/1M | $0.00/1M |
| Output Cost | $6.00/1M | $0.00/1M |
| Blended (3:1) | $3.00/1M | — |
| Specifications | ||
| Organization | Mistral | Alibaba |
| Release Date | Nov 18, 2024 | Jan 28, 2025 |
| Performance & Speed | ||
| Throughput | — | — |
| TTFT | — | — |
| Latency | — | — |
| Composite Indices | ||
| Value Score | 100.0 | — |
| Reasoning Score | 20.7 | 36.0 |
| Intelligence | 8.1 | 10.2 |
| Math | 2.3 | — |
| Standard Benchmarks | ||
| GPQA | 50.5% | 58.7% |
| MMLU Pro | 70.1% | 76.2% |
| HLE | 3.6% | 4.5% |
| LiveCodeBench | 26.1% | 35.9% |
| MATH 500 | 71.4% | 83.5% |
| AIME 2025 | 2.3% | — |
| AIME (Original) | 7.0% | 23.3% |
| SciCode | 29.2% | 33.7% |
| LCR | 10.3% | — |
| IFBench | 34.5% | — |
| TAU-bench v2 | 36.5% | — |
Key Takeaways
Qwen2.5 Max offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
Qwen2.5 Max has the strongest reasoning profile with a 36.0 reasoning score,combining the available reasoning-heavy benchmarks.
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
Qwen2.5 Max
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis