Model Comparison
Pixtral Large
vs. Qwen3 235B A22B 2507 Instruct
Comparing 2 AI models · 12 benchmarks · Mistral, Alibaba
Recommended Pick
AlQwen3 235B A22B 2507 Instruct18 metric winsStrongest on: Value, Input price, Output price
Best Value
Qwen3 235B A22B 2507 Instruct
100.0 value score
59.6 reasoning / $1.22/1M
Lowest Price
Qwen3 235B A22B 2507 Instruct
$0.70/1M input price
Best Reasoning
Qwen3 235B A22B 2507 Instruct
59.6 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
Best value
Qwen3 235B A22B 2507 Instruct has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Qwen3 235B A22B 2507 Instruct is 2.9x cheaper on input tokens than Pixtral Large.
Reasoning gap
Qwen3 235B A22B 2507 Instruct leads Pixtral Large by 38.8 points on reasoning.
Top-pick rationale
Qwen3 235B A22B 2507 Instruct wins 18 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
—
tok/s
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Tokens
—
Cost
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Qwen3 235B A22B 2507 Instruct
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 Qwen3 235B A22B 2507 Instruct |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $2.00/1M | $0.70/1M |
| Output Cost | $6.00/1M | $2.80/1M |
| Blended (3:1) | $3.00/1M | $1.22/1M |
| Specifications | ||
| Organization | Mistral | Alibaba |
| Release Date | Nov 18, 2024 | Jul 21, 2025 |
| Performance & Speed | ||
| Throughput | — | 65.2 tok/s |
| TTFT | — | 1154ms |
| Latency | — | 1154ms |
| Composite Indices | ||
| Value Score | 14.2 | 100.0 |
| Reasoning Score | 20.7 | 59.6 |
| Intelligence | 8.1 | 18.2 |
| Math | 2.3 | 71.7 |
| Standard Benchmarks | ||
| GPQA | 50.5% | 75.3% |
| MMLU Pro | 70.1% | 82.8% |
| HLE | 3.6% | 10.6% |
| LiveCodeBench | 26.1% | 52.4% |
| MATH 500 | 71.4% | 98.0% |
| AIME 2025 | 2.3% | 71.7% |
| AIME (Original) | 7.0% | 71.7% |
| SciCode | 29.2% | 36.0% |
| LCR | 10.3% | 31.2% |
| IFBench | 34.5% | 46.1% |
| TAU-bench v2 | 36.5% | 33.3% |
| TerminalBench Hard | — | 15.2% |
Key Takeaways
Qwen3 235B A22B 2507 Instruct offers the best value at $0.70/1M,making it ideal for high-volume applications and cost-conscious projects.
Qwen3 235B A22B 2507 Instruct has the strongest reasoning profile with a 59.6 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
Qwen3 235B A22B 2507 Instruct
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
