Model comparison
Mellum2-12B-A2.5B-Thinking vs Qwen3.6-35B-A3B
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Mellum2-12B-A2.5B-Thinking unranked (Not scored); Qwen3.6-35B-A3B #104 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Mellum2-12B-A2.5B-Thinking and Qwen3.6-35B-A3B share 1 comparable benchmark result. 1 of 8 categories are comparable. 4 results are unique to Mellum2-12B-A2.5B-Thinking; 56 to Qwen3.6-35B-A3B.
Updated July 23, 2026- Shared results
- 1
- Mellum2-12B-A2.5B-Thinking only
- 4
- Qwen3.6-35B-A3B only
- 56
- Comparable categories
- 1 / 8
Treat this as a split decision. Mellum2-12B-A2.5B-Thinking makes more sense if knowledge is the priority; Qwen3.6-35B-A3B is the better fit if you need the larger 262K context window.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Mellum2-12B-A2.5B-Thinking and Qwen3.6-35B-A3B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Qwen3.6-35B-A3B gives you the larger context window at 262K, compared with 128K for Mellum2-12B-A2.5B-Thinking.
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 | Mellum2-12B-A2.5B-Thinking | Δ | Qwen3.6-35B-A3B |
|---|---|---|---|
| Knowledge | Mellum2-12B-A2.5B-Thinking57.6 | Margin← 6.2 | Qwen3.6-35B-A3B51.4 |
| Agentic | Mellum2-12B-A2.5B-ThinkingNot measured | MarginNo overlap | Qwen3.6-35B-A3B51.5 |
| Coding | Mellum2-12B-A2.5B-ThinkingNot measured | MarginNo overlap | Qwen3.6-35B-A3B73.8 |
| Math | Mellum2-12B-A2.5B-ThinkingNot measured | MarginNo overlap | Qwen3.6-35B-A3B88.2 |
| Multimodal | Mellum2-12B-A2.5B-ThinkingNot measured | MarginNo overlap | Qwen3.6-35B-A3B76.3 |
| Inst. Following | Mellum2-12B-A2.5B-Thinking76.5 | MarginNo overlap | Qwen3.6-35B-A3BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 57.6%B 86%Winner: Qwen3.6-35B-A3BΔ 28.4GPQA: Mellum2-12B-A2.5B-Thinking scored 57.6%; Qwen3.6-35B-A3B scored 86%. Qwen3.6-35B-A3B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Mellum2-12B-A2.5B-Thinking | Qwen3.6-35B-A3B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Mellum2-12B-A2.5B-ThinkingNot available | Qwen3.6-35B-A3BNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Mellum2-12B-A2.5B-ThinkingNot available | Qwen3.6-35B-A3BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Mellum2-12B-A2.5B-ThinkingNot available | Qwen3.6-35B-A3BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Mellum2-12B-A2.5B-Thinking128K | Qwen3.6-35B-A3B262K | Qwen3.6-35B-A3B lists the larger context window. |
Benchmark Deep Dive
Agentic16 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Thinking | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| BFCL v4Source | 45.6% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| Claw-EvalSource | — | 68.7% | Not comparable |
| QwenClawBenchSource | — | 52.6% | Not comparable |
| QwenWebBenchSource | — | 1397 | Not comparable |
| τ³-bench resultsSource | — | 67.2% | Not comparable |
| VITA-BenchSource | — | 35.6% | Not comparable |
| DeepPlanningSource | — | 25.9% | Not comparable |
| ToolathlonSource | — | 26.9% | Not comparable |
| MCP AtlasSource | — | 62.8% | Not comparable |
| WideResearchSource | — | 60.1% | Not comparable |
| AA Agentic IndexSource | — | 21.4% | Not comparable |
| τ²-bench resultsSource | — | 95.3% | Not comparable |
| GDPval-AASource | — | 27.4% | Not comparable |
| GDPval-AASource | — | 1049 | Not comparable |
| Gert LabsSource | — | 42.65% | Not comparable |
Coding8 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Thinking | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | — | 73.4% | Not comparable |
| SWE MultilingualSource | — | 67.2% | Not comparable |
| SWE-bench ProSource | — | 49.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 51.5% | Not comparable |
| LiveCodeBenchSource | — | 80.4% | Not comparable |
| NL2RepoSource | — | 29.4% | Not comparable |
| AA Coding IndexSource | — | 41.9% | Not comparable |
| AA-SciCodeSource | — | 35.8% | Not comparable |
Reasoning2 benchmarks
KnowledgeMellum2-12B-A2.5B-Thinking wins13 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Thinking | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| MMLU-ReduxSource | 86.2% | — | Not comparable |
| GPQASource | 57.6% | 86% | Qwen3.6-35B-A3B leads |
| GPQA-DSource | 57.6% | — | Not comparable |
| MMLU-ProSource | — | 85.2% | Not comparable |
| SuperGPQASource | — | 64.7% | Not comparable |
| C-EvalSource | — | 90% | Not comparable |
| HLESource | — | 21.4% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 31.6% | Not comparable |
| AA-GPQA DiamondSource | — | 84.1% | Not comparable |
| AA-HLESource | — | 20.2% | Not comparable |
| AA-Omniscience IndexSource | — | -21.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 18.9% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 49.7% | Not comparable |
Math5 benchmarks
Multimodal15 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Thinking | Qwen3.6-35B-A3B | Result |
|---|---|---|---|
| MMMUSource | — | 81.7% | Not comparable |
| MMMU-ProSource | — | 75.3% | Not comparable |
| RealWorldQASource | — | 85.3% | Not comparable |
| OmniDocBench 1.5Source | — | 89.9% | Not comparable |
| CharXivSource | — | 78% | Not comparable |
| SimpleVQASource | — | 58.9% | Not comparable |
| CC-OCRSource | — | 81.9% | Not comparable |
| AI2D_TESTSource | — | 92.7% | Not comparable |
| RefCOCO (avg)Source | — | 92.0% | Not comparable |
| ODINW13Source | — | 50.8% | Not comparable |
| Video-MME (with subtitle)Source | — | 86.6% | Not comparable |
| Video-MME (w/o subtitle)Source | — | 82.5% | Not comparable |
| VideoMMMUSource | — | 83.7% | Not comparable |
| MLVU (M-Avg)Source | — | 86.2% | Not comparable |
| AA-MMMU-ProSource | — | 75.0% | Not comparable |
Frequently Asked Questions (2)
Which is better, Mellum2-12B-A2.5B-Thinking or Qwen3.6-35B-A3B?
Mellum2-12B-A2.5B-Thinking and Qwen3.6-35B-A3B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, Mellum2-12B-A2.5B-Thinking or Qwen3.6-35B-A3B?
Mellum2-12B-A2.5B-Thinking has the edge for knowledge tasks in this comparison, averaging 57.6 versus 51.4. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Related Comparisons
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.