Model comparison
GPT-4.1 vs Qwen3.6-27B
Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-4.1 #108 (Supported); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-4.1 and Qwen3.6-27B share 15 comparable benchmark results. 3 of 8 categories are comparable. 5 results are unique to GPT-4.1; 39 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 15
- GPT-4.1 only
- 5
- Qwen3.6-27B only
- 39
- Comparable categories
- 3 / 8
Pick Qwen3.6-27B if you want the stronger benchmark profile. GPT-4.1 only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 6 evidence categories; 3 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 has the cleaner BenchAlign overall profile here, landing at 53.82 versus 51.11. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Qwen3.6-27B's sharpest advantage is in mathematics, where it averages 89.2 against 4.1. The single biggest benchmark swing on the page is SWE-bench Verified, 54.6% to 77.2%. GPT-4.1 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 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 is the reasoning model in the pair, while GPT-4.1 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-4.1 gives you the larger context window at 1M, 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-4.1 | Δ | Qwen3.6-27B |
|---|---|---|---|
| Math | GPT-4.14.1 | Margin→ 85.1 | Qwen3.6-27B89.2 |
| Coding | GPT-4.154.6 | Margin→ 22.9 | Qwen3.6-27B77.5 |
| Knowledge | GPT-4.166.3 | Margin← 13.0 | Qwen3.6-27B53.3 |
| Agentic | GPT-4.1Not measured | MarginNo overlap | Qwen3.6-27B59.3 |
| Multimodal | GPT-4.1Not measured | MarginNo overlap | Qwen3.6-27B76.7 |
| Inst. Following | GPT-4.187.4 | MarginNo overlap | Qwen3.6-27BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 54.6%B 77.2%Winner: Qwen3.6-27BΔ 22.6SWE-bench Verified: GPT-4.1 scored 54.6%; Qwen3.6-27B scored 77.2%. Qwen3.6-27B wins this benchmark. - Source ↗
GPQA
KnowledgeA 66.3%B 87.8%Winner: Qwen3.6-27BΔ 21.5GPQA: GPT-4.1 scored 66.3%; 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 | GPT-4.1 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4.1$2 input / $8 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | GPT-4.1108 tok/s | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-4.11.02 s | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-4.11M | Qwen3.6-27B262K | GPT-4.1 lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | GPT-4.1 | Qwen3.6-27B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 47.1% | 94.2% | Qwen3.6-27B leads |
| Gert LabsSource | 25.65% | 54.84% | 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 |
CodingQwen3.6-27B wins8 benchmarks
| Benchmark | GPT-4.1 | Qwen3.6-27B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 54.6% | 77.2% | Qwen3.6-27B leads |
| AA-SciCodeSource | 38.1% | 39.8% | Qwen3.6-27B leads |
| 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
KnowledgeGPT-4.1 wins13 benchmarks
| Benchmark | GPT-4.1 | Qwen3.6-27B | Result |
|---|---|---|---|
| MMLUSource | 90.2% | — | Not comparable |
| GPQASource | 66.3% | 87.8% | Qwen3.6-27B leads |
| Artificial Analysis Intelligence IndexSource | 19.4% | 37.0% | Qwen3.6-27B leads |
| AA-GPQA DiamondSource | 66.6% | 84.2% | Qwen3.6-27B leads |
| AA-HLESource | 4.6% | 21.6% | Qwen3.6-27B leads |
| AA-Omniscience IndexSource | -36.2% | -19.8% | Qwen3.6-27B leads |
| AA-Omniscience AccuracySource | 24.2% | 19.2% | GPT-4.1 leads |
| AA-Omniscience Hallucination RateSource | 79.6% | 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 wins7 benchmarks
| Benchmark | GPT-4.1 | Qwen3.6-27B | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 5.517% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 0.000% | — | 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 | GPT-4.1 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 61.2% | 74.6% | Qwen3.6-27B leads |
| Design Arena WebsiteSource | 1068 | — | 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 |
Frequently Asked Questions (4)
Which is better, GPT-4.1 or Qwen3.6-27B?
Qwen3.6-27B is ahead on BenchLM's BenchAlign leaderboard, 53.82 to 51.11. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 54.6% and 77.2%.
Which is better for knowledge tasks, GPT-4.1 or Qwen3.6-27B?
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 66.3 versus 53.3. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-4.1 or Qwen3.6-27B?
Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 versus 54.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, GPT-4.1 or Qwen3.6-27B?
Qwen3.6-27B has the edge for math in this comparison, averaging 89.2 versus 4.1. GPT-4.1 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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