Model Comparison
Llama 3.3 Instruct 70B
vs. Qwen3.7 Max
Comparing 2 AI models · 12 benchmarks · Meta, Alibaba
Recommended Pick
Al Qwen3.7 Max 11 metric wins Strongest on: Throughput, Reasoning, Intelligence
Best Value
Llama 3.3 Instruct 70B
100.0 value score
27.3 reasoning / $0.61/1M
Lowest Price
Llama 3.3 Instruct 70B
$0.58/1M input price
Best Reasoning
Qwen3.7 Max
62.3 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3.7 Max
50.1 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
Llama 3.3 Instruct 70B has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Llama 3.3 Instruct 70B is 4.3x cheaper on input tokens than Qwen3.7 Max.
Speed gap
Qwen3.7 Max generates about 2.0x as many tokens per second as Llama 3.3 Instruct 70B.
Reasoning gap
Qwen3.7 Max leads Llama 3.3 Instruct 70B by 35.1 points on reasoning.
Coding gap
Qwen3.7 Max leads Llama 3.3 Instruct 70B by 39.4 points on coding.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Llama 3.3 Instruct 70B
Meta
TTFT
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Time
—
tok/s
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Tokens
—
Cost
—
Qwen3.7 Max
Alibaba
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Me Llama 3.3 Instruct 70B | Top Pick Al Qwen3.7 Max |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.58/1M | $2.50/1M |
| Output Cost | $0.71/1M | $7.50/1M |
| Blended (3:1) | $0.61/1M | $3.75/1M |
| Specifications | ||
| Organization | Meta | Alibaba |
| Release Date | Dec 6, 2024 | May 19, 2026 |
| Performance & Speed | ||
| Throughput | 94.5 tok/s | 187.7 tok/s |
| TTFT | 648ms | 1591ms |
| Latency | 648ms | 14425ms |
| Composite Indices | ||
| Value Score | 100.0 | 37.3 |
| Reasoning Score | 27.3 | 62.3 |
| Intelligence | 14.5 | 56.6 |
| Coding | 10.7 | 50.1 |
| Math | 7.7 | — |
| Standard Benchmarks | ||
| GPQA | 49.8% | 92.3% |
| MMLU Pro | 71.3% | — |
| HLE | 4.0% | 38.1% |
| LiveCodeBench | 28.8% | — |
| MATH 500 | 77.3% | — |
| AIME 2025 | 7.7% | — |
| AIME (Original) | 30.0% | — |
| SciCode | 26.0% | 48.8% |
| LCR | 15.0% | 69.0% |
| IFBench | 47.1% | 80.5% |
| TAU-bench v2 | 26.6% | 94.7% |
| TerminalBench Hard | 3.0% | 50.8% |
Key Takeaways
Llama 3.3 Instruct 70B offers the best value at $0.58/1M, making it ideal for high-volume applications and cost-conscious projects.
Qwen3.7 Max has the strongest reasoning profile with a 62.3 reasoning score, combining the available reasoning-heavy benchmarks.
Qwen3.7 Max reaches a 50.1 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 3.3 Instruct 70B
- Cost-sensitive applications
- High-volume processing
Qwen3.7 Max
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
