Model comparison
Moonshot v1 vs Qwen3.6-27B
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Moonshot v1 #148 (Estimated); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Moonshot v1 and Qwen3.6-27B share 0 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to Moonshot v1; 54 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 0
- Moonshot v1 only
- 0
- Qwen3.6-27B only
- 54
- Comparable categories
- 0 / 8
Benchmark data for Moonshot v1 and Qwen3.6-27B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM does not have sourced benchmark coverage for Moonshot v1 yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Qwen3.6-27B has the larger context window at 262K, compared with 128K for Moonshot v1.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Moonshot v1 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Moonshot v1Not available | Qwen3.6-27B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | Moonshot v1Not available | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Moonshot v1Not available | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Moonshot v1128K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | Moonshot v1 | Qwen3.6-27B | Result |
|---|---|---|---|
| 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 |
| τ²-bench resultsSource | — | 94.2% | Not comparable |
| GDPval-AASource | — | 32.0% | Not comparable |
| GDPval-AASource | — | 1140 | Not comparable |
| Gert LabsSource | — | 54.84% | Not comparable |
Coding8 benchmarks
| Benchmark | Moonshot v1 | Qwen3.6-27B | Result |
|---|---|---|---|
| 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 |
| AA-SciCodeSource | — | 39.8% | Not comparable |
Reasoning2 benchmarks
Knowledge12 benchmarks
| Benchmark | Moonshot v1 | Qwen3.6-27B | Result |
|---|---|---|---|
| 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 |
| Artificial Analysis Intelligence IndexSource | — | 37.0% | Not comparable |
| AA-GPQA DiamondSource | — | 84.2% | Not comparable |
| AA-HLESource | — | 21.6% | Not comparable |
| AA-Omniscience IndexSource | — | -19.8% | Not comparable |
| AA-Omniscience AccuracySource | — | 19.2% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 48.3% | Not comparable |
Math5 benchmarks
Multimodal16 benchmarks
| Benchmark | Moonshot v1 | 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 |
Inst. Following1 benchmarks
| Benchmark | Moonshot v1 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 67.6% | Not comparable |
Frequently Asked Questions (3)
Can I compare Moonshot v1 and Qwen3.6-27B on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Moonshot v1 and Qwen3.6-27B today?
Moonshot v1: Pricing unavailable Qwen3.6-27B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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