Model Comparison
3.5 (1210)
vs. Qwen3 0.6B (Reasoning)
Comparing 2 AI models · 12 benchmarks · OpenChat, Alibaba
Recommended Pick
AlQwen3 0.6B (Reasoning)7 metric winsStrongest on: Reasoning, GPQA, MMLU Pro
Lowest Price
3.5 (1210)
$0.00/1M input price
Best Reasoning
Qwen3 0.6B (Reasoning)
21.7 reasoning score
Blends available reasoning benchmarks
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Reasoning gap
Qwen3 0.6B (Reasoning) leads 3.5 (1210) by 9.4 points on reasoning.
Top-pick rationale
Qwen3 0.6B (Reasoning) wins 7 measurable categories, including Reasoning, GPQA, MMLU Pro, HLE.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
3.5 (1210)
OpenChat
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 0.6B (Reasoning)
Alibaba
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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Which answer was more useful?
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Full Comparison
| Metric | Op 3.5 (1210) | Top Pick Al Qwen3 0.6B (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.00/1M |
| Output Cost | $0.00/1M | $0.00/1M |
| Specifications | ||
| Organization | OpenChat | Alibaba |
| Release Date | Dec 18, 2023 | Apr 28, 2025 |
| Performance & Speed | ||
| Throughput | — | — |
| TTFT | — | — |
| Latency | — | — |
| Composite Indices | ||
| Reasoning Score | 12.3 | 21.7 |
| Intelligence | 3.0 | 1.3 |
| Math | — | 18.0 |
| Standard Benchmarks | ||
| GPQA | 23.0% | 23.9% |
| MMLU Pro | 31.0% | 34.7% |
| HLE | 4.8% | 5.7% |
| LiveCodeBench | 11.5% | 12.1% |
| MATH 500 | 30.7% | 75.0% |
| AIME 2025 | — | 18.0% |
| AIME (Original) | 0.0% | 10.0% |
| SciCode | — | 2.8% |
| LCR | — | 0.0% |
| IFBench | — | 23.3% |
| TAU-bench v2 | — | 21.1% |
| TerminalBench Hard | — | 0.0% |
Key Takeaways
3.5 (1210) offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
Qwen3 0.6B (Reasoning) has the strongest reasoning profile with a 21.7 reasoning score,combining the available reasoning-heavy benchmarks.
All models support context windows of ∞+ tokens,suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
3.5 (1210)
- Cost-sensitive applications
- High-volume processing
Qwen3 0.6B (Reasoning)
- Complex reasoning tasks
- Research & analysis
