Model Comparison
R1 Distill Llama 70B
vs. Qwen3.5 122B A10B (Reasoning)
Comparing 2 AI models · 12 benchmarks · DeepSeek, Alibaba
Recommended Pick
Al Qwen3.5 122B A10B (Reasoning) 13 metric wins Strongest on: Input price, Throughput, Latency
Best Value
R1 Distill Llama 70B
100.0 value score
47.2 reasoning / $0.79/1M
Lowest Price
Qwen3.5 122B A10B (Reasoning)
$0.40/1M input price
Best Reasoning
Qwen3.5 122B A10B (Reasoning)
50.2 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3.5 122B A10B (Reasoning)
34.7 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
R1 Distill Llama 70B has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Qwen3.5 122B A10B (Reasoning) is 1.7x cheaper on input tokens than R1 Distill Llama 70B.
Speed gap
Qwen3.5 122B A10B (Reasoning) generates about 3.2x as many tokens per second as R1 Distill Llama 70B.
Reasoning gap
Qwen3.5 122B A10B (Reasoning) leads R1 Distill Llama 70B by 3.1 points on reasoning.
Coding gap
Qwen3.5 122B A10B (Reasoning) leads R1 Distill Llama 70B by 23.3 points on coding.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
R1 Distill Llama 70B
DeepSeek
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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Qwen3.5 122B A10B (Reasoning)
Alibaba
TTFT
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Time
—
tok/s
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Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | De R1 Distill Llama 70B | Top Pick Al Qwen3.5 122B A10B (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.70/1M | $0.40/1M |
| Output Cost | $1.05/1M | $3.20/1M |
| Blended (3:1) | $0.79/1M | $1.10/1M |
| Specifications | ||
| Organization | DeepSeek | Alibaba |
| Release Date | Jan 20, 2025 | Feb 24, 2026 |
| Performance & Speed | ||
| Throughput | 45.5 tok/s | 147.3 tok/s |
| TTFT | 415ms | 1165ms |
| Latency | 44390ms | 14743ms |
| Composite Indices | ||
| Value Score | 100.0 | 76.3 |
| Reasoning Score | 47.2 | 50.2 |
| Intelligence | 16.0 | 41.6 |
| Coding | 11.4 | 34.7 |
| Math | 53.7 | — |
| Standard Benchmarks | ||
| GPQA | 40.2% | 85.7% |
| MMLU Pro | 79.5% | — |
| HLE | 6.1% | 23.4% |
| LiveCodeBench | 26.6% | — |
| MATH 500 | 93.5% | — |
| AIME 2025 | 53.7% | — |
| AIME (Original) | 67.0% | — |
| SciCode | 31.3% | 42.0% |
| LCR | 11.0% | 66.7% |
| IFBench | 27.6% | 75.7% |
| TAU-bench v2 | 21.9% | 93.6% |
| TerminalBench Hard | 1.5% | 31.1% |
Key Takeaways
Qwen3.5 122B A10B (Reasoning) offers the best value at $0.40/1M, making it ideal for high-volume applications and cost-conscious projects.
Qwen3.5 122B A10B (Reasoning) has the strongest reasoning profile with a 50.2 reasoning score, combining the available reasoning-heavy benchmarks.
Qwen3.5 122B A10B (Reasoning) reaches a 34.7 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
R1 Distill Llama 70B
- General-purpose AI
- Versatile applications
Qwen3.5 122B A10B (Reasoning)
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
