Model comparison
o1 vs Qwen3.6-27B
Head-to-head evidence from 13 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: o1 #129 (Estimated); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. o1 and Qwen3.6-27B share 13 comparable benchmark results. 2 of 8 categories are comparable. 3 results are unique to o1; 41 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 13
- o1 only
- 3
- Qwen3.6-27B only
- 41
- Comparable categories
- 2 / 8
Pick Qwen3.6-27B if you want the stronger benchmark profile. o1 only becomes the better choice if knowledge is the priority.
Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 5 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Qwen3.6-27B is clearly ahead on the BenchAlign aggregate, 53.82 to 48.1. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.6-27B's sharpest advantage is in mathematics, where it averages 89.2 against 9.3. The single biggest benchmark swing on the page is GPQA, 75.7% to 87.8%. o1 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B gives you the larger context window at 262K, compared with 200K for o1.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | o1 | Δ | Qwen3.6-27B |
|---|---|---|---|
| Math | o19.3 | Margin→ 79.9 | Qwen3.6-27B89.2 |
| Knowledge | o175.7 | Margin← 22.4 | Qwen3.6-27B53.3 |
| Agentic | o1Not measured | MarginNo overlap | Qwen3.6-27B59.3 |
| Coding | o1Not measured | MarginNo overlap | Qwen3.6-27B77.5 |
| Multimodal | o1Not measured | MarginNo overlap | Qwen3.6-27B76.7 |
| Inst. Following | o192.2 | MarginNo overlap | Qwen3.6-27BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 75.7%B 87.8%Winner: Qwen3.6-27BΔ 12.1GPQA: o1 scored 75.7%; Qwen3.6-27B scored 87.8%. Qwen3.6-27B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | o1 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | o1$15 input / $60 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | o198 tok/s | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | o132.29 s | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | o1200K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | o1 | Qwen3.6-27B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 62.6% | 94.2% | Qwen3.6-27B leads |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| Claw-EvalSource | — | 72.4% | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
| AA Agentic IndexSource | — | 27.0% | Not comparable |
| GDPval-AASource | — | 32.0% | Not comparable |
| GDPval-AASource | — | 1140 | Not comparable |
| Gert LabsSource | — | 54.84% | Not comparable |
Coding8 benchmarks
| Benchmark | o1 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA Coding IndexSource | 39.7% | 53.7% | Qwen3.6-27B leads |
| AA-SciCodeSource | 35.8% | 39.8% | Qwen3.6-27B leads |
| SWE-bench VerifiedSource | — | 77.2% | Not comparable |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| SWE-bench ProSource | — | 53.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
Reasoning2 benchmarks
Knowledgeo1 wins13 benchmarks
| Benchmark | o1 | Qwen3.6-27B | Result |
|---|---|---|---|
| MMLUSource | 91.8% | — | Not comparable |
| GPQASource | 75.7% | 87.8% | Qwen3.6-27B leads |
| Artificial Analysis Intelligence IndexSource | 23.4% | 37.0% | Qwen3.6-27B leads |
| AA-GPQA DiamondSource | 74.7% | 84.2% | Qwen3.6-27B leads |
| AA-HLESource | 7.7% | 21.6% | Qwen3.6-27B leads |
| AA-Omniscience IndexSource | -10.5% | -19.8% | o1 leads |
| AA-Omniscience AccuracySource | 34.7% | 19.2% | o1 leads |
| AA-Omniscience Hallucination RateSource | 69.3% | 48.3% | Qwen3.6-27B leads |
| MMLU-ProSource | — | 86.2% | Not comparable |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| HLESource | — | 24% | Not comparable |
MathQwen3.6-27B wins6 benchmarks
Multimodal16 benchmarks
| Benchmark | o1 | Qwen3.6-27B | Result |
|---|---|---|---|
| MMMUSource | — | 82.9% | Not comparable |
| MMMU-ProSource | — | 75.8% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CharXivSource | — | 78.4% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| ERQASource | — | 62.5% | Not comparable |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| VideoMMMUSource | — | 84.4% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
| AA-MMMU-ProSource | — | 74.6% | Not comparable |
Frequently Asked Questions (3)
Which is better, o1 or Qwen3.6-27B?
Qwen3.6-27B is ahead on BenchLM's BenchAlign leaderboard, 53.82 to 48.1. The biggest single separator in this matchup is GPQA, where the scores are 75.7% and 87.8%.
Which is better for knowledge tasks, o1 or Qwen3.6-27B?
o1 has the edge for knowledge tasks in this comparison, averaging 75.7 versus 53.3. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for math, o1 or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 9.3. o1 stays close enough that the answer can still flip depending on your workload.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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