Model Comparison
Qwen3 235B A22B 2507 (Reasoning)
vs. Seed-OSS-36B-Instruct
Comparing 2 AI models · 12 benchmarks · Alibaba, ByteDance Seed
Recommended Pick
AlQwen3 235B A22B 2507 (Reasoning)16 metric winsStrongest on: Throughput, TTFT, Latency
Best Value
Seed-OSS-36B-Instruct
100.0 value score
53.9 reasoning / $0.30/1M
Lowest Price
Seed-OSS-36B-Instruct
$0.21/1M input price
Best Reasoning
Qwen3 235B A22B 2507 (Reasoning)
69.7 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3 235B A22B 2507 (Reasoning)
22.1 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
Seed-OSS-36B-Instruct has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Seed-OSS-36B-Instruct is 3.3x cheaper on input tokens than Qwen3 235B A22B 2507 (Reasoning).
Speed gap
Qwen3 235B A22B 2507 (Reasoning) generates about 1.8x as many tokens per second as Seed-OSS-36B-Instruct.
Reasoning gap
Qwen3 235B A22B 2507 (Reasoning) leads Seed-OSS-36B-Instruct by 15.8 points on reasoning.
Top-pick rationale
Qwen3 235B A22B 2507 (Reasoning) wins 16 measurable categories, including Throughput, TTFT, Latency, Reasoning.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Qwen3 235B A22B 2507 (Reasoning)
Alibaba
TTFT
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Seed-OSS-36B-Instruct
ByteDance Seed
TTFT
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tok/s
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Which answer was more useful?
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Full Comparison
| Metric | Top Pick Al Qwen3 235B A22B 2507 (Reasoning) | By Seed-OSS-36B-Instruct |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.70/1M | $0.21/1M |
| Output Cost | $8.40/1M | $0.57/1M |
| Blended (3:1) | $2.63/1M | $0.30/1M |
| Specifications | ||
| Organization | Alibaba | ByteDance Seed |
| Release Date | Jul 25, 2025 | Aug 20, 2025 |
| Performance & Speed | ||
| Throughput | 68.3 tok/s | 38.7 tok/s |
| TTFT | 1275ms | 1478ms |
| Latency | 30569ms | 53149ms |
| Composite Indices | ||
| Value Score | 14.8 | 100.0 |
| Reasoning Score | 69.7 | 53.9 |
| Intelligence | 19.6 | 18.3 |
| Coding | 22.1 | — |
| Math | 91.0 | 84.7 |
| Standard Benchmarks | ||
| GPQA | 79.0% | 72.6% |
| MMLU Pro | 84.3% | 81.5% |
| HLE | 15.0% | 9.1% |
| LiveCodeBench | 78.8% | 76.5% |
| MATH 500 | 98.4% | — |
| AIME 2025 | 91.0% | 84.7% |
| AIME (Original) | 94.0% | — |
| SciCode | 42.4% | 36.5% |
| LCR | 67.0% | 57.7% |
| IFBench | 51.2% | 41.9% |
| TAU-bench v2 | 53.2% | 49.4% |
| TerminalBench Hard | 13.6% | 6.8% |
Key Takeaways
Seed-OSS-36B-Instruct offers the best value at $0.21/1M,making it ideal for high-volume applications and cost-conscious projects.
Qwen3 235B A22B 2507 (Reasoning) has the strongest reasoning profile with a 69.7 reasoning score,combining the available reasoning-heavy benchmarks.
Qwen3 235B A22B 2507 (Reasoning) reaches a 22.1 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
Qwen3 235B A22B 2507 (Reasoning)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
Seed-OSS-36B-Instruct
- Cost-sensitive applications
- High-volume processing
