Model Comparison
Pixtral Large
vs. Qwen3 14B (Reasoning)
Comparing 2 AI models · 12 benchmarks · Mistral, Alibaba
Recommended Pick
AlQwen3 14B (Reasoning)17 metric winsStrongest on: Value, Input price, Output price
Best Value
Qwen3 14B (Reasoning)
100.0 value score
51.3 reasoning / $1.31/1M
Lowest Price
Qwen3 14B (Reasoning)
$0.35/1M input price
Best Reasoning
Qwen3 14B (Reasoning)
51.3 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3 14B (Reasoning)
13.8 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 14B (Reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Qwen3 14B (Reasoning) is 5.7x cheaper on input tokens than Pixtral Large.
Reasoning gap
Qwen3 14B (Reasoning) leads Pixtral Large by 30.5 points on reasoning.
Top-pick rationale
Qwen3 14B (Reasoning) wins 17 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 14B (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 14B (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $2.00/1M | $0.35/1M |
| Output Cost | $6.00/1M | $4.20/1M |
| Blended (3:1) | $3.00/1M | $1.31/1M |
| Specifications | ||
| Organization | Mistral | Alibaba |
| Release Date | Nov 18, 2024 | Apr 28, 2025 |
| Performance & Speed | ||
| Throughput | — | 63.9 tok/s |
| TTFT | — | 1133ms |
| Latency | — | 32440ms |
| Composite Indices | ||
| Value Score | 17.7 | 100.0 |
| Reasoning Score | 20.7 | 51.3 |
| Intelligence | 8.1 | 10.4 |
| Coding | — | 13.8 |
| Math | 2.3 | 55.7 |
| Standard Benchmarks | ||
| GPQA | 50.5% | 60.4% |
| MMLU Pro | 70.1% | 77.4% |
| HLE | 3.6% | 4.3% |
| LiveCodeBench | 26.1% | 52.3% |
| MATH 500 | 71.4% | 96.1% |
| AIME 2025 | 2.3% | 55.7% |
| AIME (Original) | 7.0% | 76.3% |
| SciCode | 29.2% | 31.6% |
| LCR | 10.3% | 0.0% |
| IFBench | 34.5% | 40.5% |
| TAU-bench v2 | 36.5% | 34.5% |
| TerminalBench Hard | — | 3.8% |
Key Takeaways
Qwen3 14B (Reasoning) offers the best value at $0.35/1M,making it ideal for high-volume applications and cost-conscious projects.
Qwen3 14B (Reasoning) has the strongest reasoning profile with a 51.3 reasoning score,combining the available reasoning-heavy benchmarks.
Qwen3 14B (Reasoning) reaches a 13.8 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 14B (Reasoning)
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
