Model comparison
o3 vs Qwen3.6-27B
Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: o3 #131 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. o3 and Qwen3.6-27B share 12 comparable benchmark results. 1 of 8 categories are comparable. 4 results are unique to o3; 42 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 12
- o3 only
- 4
- Qwen3.6-27B only
- 42
- Comparable categories
- 1 / 8
Pick Qwen3.6-27B if you want the stronger benchmark profile. o3 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 evidence categories; 1 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 47.89. 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 14.5.
o3 is also the more expensive model on tokens at $2.00 input / $8.00 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 o3.
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 | o3 | Δ | Qwen3.6-27B |
|---|---|---|---|
| Math | o314.5 | Margin→ 74.7 | Qwen3.6-27B89.2 |
| Agentic | o3Not measured | MarginNo overlap | Qwen3.6-27B59.3 |
| Coding | o3Not measured | MarginNo overlap | Qwen3.6-27B77.5 |
| Knowledge | o3Not measured | MarginNo overlap | Qwen3.6-27B53.3 |
| Multimodal | o3Not measured | MarginNo overlap | Qwen3.6-27B76.7 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | o3 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | o3$2 input / $8 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | o3118 tok/s | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | o35.38 s | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | o3200K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | o3 | Qwen3.6-27B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 80.7% | 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 | o3 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-SciCodeSource | 41.0% | 39.8% | o3 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 |
| AA Coding IndexSource | — | 53.7% | Not comparable |
Reasoning2 benchmarks
Knowledge12 benchmarks
| Benchmark | o3 | Qwen3.6-27B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 30.4% | 37.0% | Qwen3.6-27B leads |
| AA-GPQA DiamondSource | 82.7% | 84.2% | Qwen3.6-27B leads |
| AA-HLESource | 20.0% | 21.6% | Qwen3.6-27B leads |
| AA-Omniscience IndexSource | -15.3% | -19.8% | o3 leads |
| AA-Omniscience AccuracySource | 38.4% | 19.2% | o3 leads |
| AA-Omniscience Hallucination RateSource | 87.1% | 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 |
| GPQASource | — | 87.8% | Not comparable |
| HLESource | — | 24% | Not comparable |
MathQwen3.6-27B wins8 benchmarks
| Benchmark | o3 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA MATH-500Source | 99.2% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 18.685% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 2.083% | — | Not comparable |
| HMMT Feb 2025Source | — | 93.8% | Not comparable |
| HMMT Nov 2025Source | — | 90.7% | Not comparable |
| HMMT Feb 2026Source | — | 84.3% | Not comparable |
| MMAnswerBenchSource | — | 80.8% | Not comparable |
| AIME26Source | — | 94.1% | Not comparable |
Multimodal17 benchmarks
| Benchmark | o3 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 70.1% | 74.6% | Qwen3.6-27B leads |
| Design Arena WebsiteSource | 1067 | — | Not comparable |
| 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 |
Inst. Following1 benchmarks
| Benchmark | o3 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | 71.4% | 67.6% | o3 leads |
Frequently Asked Questions (2)
Which is better, o3 or Qwen3.6-27B?
Qwen3.6-27B is ahead on BenchLM's BenchAlign leaderboard, 53.82 to 47.89.
Which is better for math, o3 or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 14.5. o3 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.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.