Model comparison
GPT-5.4 mini vs Qwen3.6-27B
Head-to-head evidence from 20 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.4 mini #75 (Estimated); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.4 mini and Qwen3.6-27B share 20 comparable benchmark results. 4 of 8 categories are comparable. 10 results are unique to GPT-5.4 mini; 34 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 20
- GPT-5.4 mini only
- 10
- Qwen3.6-27B only
- 34
- Comparable categories
- 4 / 8
Pick GPT-5.4 mini if you want the stronger benchmark profile. Qwen3.6-27B only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 20 shared benchmark results across 6 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.4 mini has the cleaner BenchAlign overall profile here, landing at 56.77 versus 53.82. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-5.4 mini's sharpest advantage is in agentic, where it averages 65.7 against 59.3. The single biggest benchmark swing on the page is HLE, 41.5% to 24%. Qwen3.6-27B does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
GPT-5.4 mini is also the more expensive model on tokens at $0.75 input / $4.50 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. GPT-5.4 mini gives you the larger context window at 400K, compared with 262K for Qwen3.6-27B.
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 | GPT-5.4 mini | Δ | Qwen3.6-27B |
|---|---|---|---|
| Math | GPT-5.4 mini21.7 | Margin→ 67.5 | Qwen3.6-27B89.2 |
| Agentic | GPT-5.4 mini65.7 | Margin← 6.4 | Qwen3.6-27B59.3 |
| Knowledge | GPT-5.4 mini47.8 | Margin→ 5.5 | Qwen3.6-27B53.3 |
| Multimodal | GPT-5.4 mini76.6 | Margin→ 0.1 | Qwen3.6-27B76.7 |
| Coding | GPT-5.4 miniNot measured | MarginNo overlap | Qwen3.6-27B77.5 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 41.5%B 24%Winner: GPT-5.4 miniΔ 17.5HLE: GPT-5.4 mini scored 41.5%; Qwen3.6-27B scored 24%. GPT-5.4 mini wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 76.6%B 75.8%Winner: GPT-5.4 miniΔ 0.8MMMU-Pro: GPT-5.4 mini scored 76.6%; Qwen3.6-27B scored 75.8%. GPT-5.4 mini wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 60%B 59.3%Winner: GPT-5.4 miniΔ 0.7Terminal-Bench 2.0: GPT-5.4 mini scored 60%; Qwen3.6-27B scored 59.3%. GPT-5.4 mini wins this benchmark. - Source ↗
GPQA
KnowledgeA 88%B 87.8%Winner: GPT-5.4 miniΔ 0.2GPQA: GPT-5.4 mini scored 88%; Qwen3.6-27B scored 87.8%. GPT-5.4 mini wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.4 mini | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.4 mini$0.75 input / $4.5 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.4 mini201 tok/s | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.4 mini3.85 s | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.4 mini400K | Qwen3.6-27B262K | GPT-5.4 mini lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.4 mini wins14 benchmarks
| Benchmark | GPT-5.4 mini | Qwen3.6-27B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 60% | 59.3% | GPT-5.4 mini leads |
| OSWorld-VerifiedSource | 72.1% | — | Not comparable |
| MCP AtlasSource | 57.7% | — | Not comparable |
| ToolathlonSource | 42.9% | — | Not comparable |
| τ²-bench resultsSource | 83.3% | 94.2% | Qwen3.6-27B leads |
| AA Agentic IndexSource | 30.2% | 27.0% | GPT-5.4 mini leads |
| APEX-Agents-AASource | 28.2% | — | Not comparable |
| GDPval-AASource | 33.6% | 32.0% | GPT-5.4 mini leads |
| GDPval-AASource | 1171 | 1140 | GPT-5.4 mini leads |
| Claw-EvalSource | — | 72.4% | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
| Gert LabsSource | — | 54.84% | Not comparable |
Coding10 benchmarks
| Benchmark | GPT-5.4 mini | Qwen3.6-27B | Result |
|---|---|---|---|
| Vibe Code BenchSource | 47.97% | — | Not comparable |
| AA Coding IndexSource | 56.1% | 53.7% | GPT-5.4 mini leads |
| AA-SciCodeSource | 49.9% | 39.8% | GPT-5.4 mini leads |
| FrontierCode 1.1 MainSource | 27.0% | — | Not comparable |
| 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
KnowledgeQwen3.6-27B wins13 benchmarks
| Benchmark | GPT-5.4 mini | Qwen3.6-27B | Result |
|---|---|---|---|
| GPQASource | 88% | 87.8% | GPT-5.4 mini leads |
| HLESource | 41.5% | 24% | GPT-5.4 mini leads |
| HLE w/o toolsSource | 28.2% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 40.0% | 37.0% | GPT-5.4 mini leads |
| AA-GPQA DiamondSource | 87.5% | 84.2% | GPT-5.4 mini leads |
| AA-HLESource | 26.6% | 21.6% | GPT-5.4 mini leads |
| AA-Omniscience IndexSource | -18.7% | -19.8% | GPT-5.4 mini leads |
| AA-Omniscience AccuracySource | 37.5% | 19.2% | GPT-5.4 mini leads |
| AA-Omniscience Hallucination RateSource | 89.8% | 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 |
MathQwen3.6-27B wins7 benchmarks
| Benchmark | GPT-5.4 mini | Qwen3.6-27B | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 28.280% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 2.080% | — | 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 |
MultimodalQwen3.6-27B wins17 benchmarks
| Benchmark | GPT-5.4 mini | Qwen3.6-27B | Result |
|---|---|---|---|
| MMMU-ProSource | 76.6% | 75.8% | GPT-5.4 mini leads |
| MMMU-Pro w/ PythonSource | 78% | — | Not comparable |
| AA-MMMU-ProSource | 73.3% | 74.6% | Qwen3.6-27B leads |
| MMMUSource | — | 82.9% | 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 | GPT-5.4 mini | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.3% | 67.6% | GPT-5.4 mini leads |
Frequently Asked Questions (5)
Which is better, GPT-5.4 mini or Qwen3.6-27B?
GPT-5.4 mini is ahead on BenchLM's BenchAlign leaderboard, 56.77 to 53.82. The biggest single separator in this matchup is HLE, where the scores are 41.5% and 24%.
Which is better for knowledge tasks, GPT-5.4 mini or Qwen3.6-27B?
Qwen3.6-27B has the edge for knowledge tasks in this comparison, averaging 53.3 versus 47.8. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for math, GPT-5.4 mini or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 21.7. GPT-5.4 mini stays close enough that the answer can still flip depending on your workload.
Which is better for agentic tasks, GPT-5.4 mini or Qwen3.6-27B?
GPT-5.4 mini has the edge for agentic tasks in this comparison, averaging 65.7 versus 59.3. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.4 mini or Qwen3.6-27B?
Qwen3.6-27B has the edge for multimodal and grounded tasks in this comparison, averaging 76.7 versus 76.6. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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