Model Comparison
Llama 3.1 Instruct 70B
vs. Qwen3 32B (Non-reasoning)
Comparing 2 AI models · 12 benchmarks · Meta, Alibaba
Recommended Pick
Al Qwen3 32B (Non-reasoning) 14 metric wins Strongest on: Value, Input price, Blended price
Best Value
Qwen3 32B (Non-reasoning)
100.0 value score
32.7 reasoning / $0.26/1M
Lowest Price
Qwen3 32B (Non-reasoning)
$0.15/1M input price
Best Reasoning
Qwen3 32B (Non-reasoning)
32.7 reasoning score
Blends available reasoning benchmarks
Best for Coding
Llama 3.1 Instruct 70B
10.9 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 32B (Non-reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Qwen3 32B (Non-reasoning) is 3.7x cheaper on input tokens than Llama 3.1 Instruct 70B.
Speed gap
Qwen3 32B (Non-reasoning) generates about 1.7x as many tokens per second as Llama 3.1 Instruct 70B.
Reasoning gap
Qwen3 32B (Non-reasoning) leads Llama 3.1 Instruct 70B by 11.5 points on reasoning.
Top-pick rationale
Qwen3 32B (Non-reasoning) wins 14 measurable categories, including Value, Input price, Blended price, Throughput.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Llama 3.1 Instruct 70B
Meta
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 32B (Non-reasoning)
Alibaba
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Me Llama 3.1 Instruct 70B | Top Pick Al Qwen3 32B (Non-reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.56/1M | $0.15/1M |
| Output Cost | $0.56/1M | $0.59/1M |
| Blended (3:1) | $0.56/1M | $0.26/1M |
| Specifications | ||
| Organization | Meta | Alibaba |
| Release Date | Jul 23, 2024 | Apr 28, 2025 |
| Performance & Speed | ||
| Throughput | 40.3 tok/s | 67.0 tok/s |
| TTFT | 546ms | 1235ms |
| Latency | 546ms | 1235ms |
| Composite Indices | ||
| Value Score | 30.1 | 100.0 |
| Reasoning Score | 21.2 | 32.7 |
| Intelligence | 12.5 | 14.5 |
| Coding | 10.9 | — |
| Math | 4.0 | 19.7 |
| Standard Benchmarks | ||
| GPQA | 40.9% | 53.5% |
| MMLU Pro | 67.6% | 72.7% |
| HLE | 4.6% | 4.3% |
| LiveCodeBench | 23.2% | 28.8% |
| MATH 500 | 64.9% | 86.9% |
| AIME 2025 | 4.0% | 19.7% |
| AIME (Original) | 17.3% | 30.3% |
| SciCode | 26.7% | 28.0% |
| LCR | 6.3% | 0.0% |
| IFBench | 34.4% | 31.5% |
| TAU-bench v2 | 15.2% | — |
| TerminalBench Hard | 3.0% | — |
Key Takeaways
Qwen3 32B (Non-reasoning) offers the best value at $0.15/1M, making it ideal for high-volume applications and cost-conscious projects.
Qwen3 32B (Non-reasoning) has the strongest reasoning profile with a 32.7 reasoning score, combining the available reasoning-heavy benchmarks.
Llama 3.1 Instruct 70B reaches a 10.9 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
Llama 3.1 Instruct 70B
- Code generation
- Software development
Qwen3 32B (Non-reasoning)
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
