Model comparison
Mellum2-12B-A2.5B-Thinking vs Qwen3.5-122B-A10B
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Mellum2-12B-A2.5B-Thinking unranked (Not scored); Qwen3.5-122B-A10B #47 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Mellum2-12B-A2.5B-Thinking and Qwen3.5-122B-A10B share 2 comparable benchmark results. 2 of 8 categories are comparable. 3 results are unique to Mellum2-12B-A2.5B-Thinking; 29 to Qwen3.5-122B-A10B.
Updated July 23, 2026- Shared results
- 2
- Mellum2-12B-A2.5B-Thinking only
- 3
- Qwen3.5-122B-A10B only
- 29
- Comparable categories
- 2 / 8
Treat this as a split decision. Mellum2-12B-A2.5B-Thinking makes more sense if its workflow fits your team better; Qwen3.5-122B-A10B is the better fit if knowledge is the priority or you need the larger 262K context window.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 evidence categories; 2 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 Qwen3.5-122B-A10B 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.
Qwen3.5-122B-A10B 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 | Qwen3.5-122B-A10B |
|---|---|---|---|
| Knowledge | Mellum2-12B-A2.5B-Thinking57.6 | Margin→ 26.0 | Qwen3.5-122B-A10B83.6 |
| Inst. Following | Mellum2-12B-A2.5B-Thinking76.5 | Margin→ 16.9 | Qwen3.5-122B-A10B93.4 |
| Agentic | Mellum2-12B-A2.5B-ThinkingNot measured | MarginNo overlap | Qwen3.5-122B-A10B56.4 |
| Coding | Mellum2-12B-A2.5B-ThinkingNot measured | MarginNo overlap | Qwen3.5-122B-A10B72.0 |
| Reasoning | Mellum2-12B-A2.5B-ThinkingNot measured | MarginNo overlap | Qwen3.5-122B-A10B60.2 |
| Multilingual | Mellum2-12B-A2.5B-ThinkingNot measured | MarginNo overlap | Qwen3.5-122B-A10B82.2 |
| Multimodal | Mellum2-12B-A2.5B-ThinkingNot measured | MarginNo overlap | Qwen3.5-122B-A10B77.2 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 57.6%B 86.6%Winner: Qwen3.5-122B-A10BΔ 29GPQA: Mellum2-12B-A2.5B-Thinking scored 57.6%; Qwen3.5-122B-A10B scored 86.6%. Qwen3.5-122B-A10B wins this benchmark. - Source ↗
IFEval
Inst. FollowingA 76.5%B 93.4%Winner: Qwen3.5-122B-A10BΔ 16.9IFEval: Mellum2-12B-A2.5B-Thinking scored 76.5%; Qwen3.5-122B-A10B scored 93.4%. Qwen3.5-122B-A10B 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 | Qwen3.5-122B-A10B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Mellum2-12B-A2.5B-ThinkingNot available | Qwen3.5-122B-A10B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | Mellum2-12B-A2.5B-ThinkingNot available | Qwen3.5-122B-A10BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Mellum2-12B-A2.5B-ThinkingNot available | Qwen3.5-122B-A10BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Mellum2-12B-A2.5B-Thinking128K | Qwen3.5-122B-A10B262K | Qwen3.5-122B-A10B lists the larger context window. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Thinking | Qwen3.5-122B-A10B | Result |
|---|---|---|---|
| BFCL v4Source | 45.6% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 49.4% | Not comparable |
| BrowseCompSource | — | 63.8% | Not comparable |
| OSWorld-VerifiedSource | — | 58% | Not comparable |
| τ²-bench resultsSource | — | 93.6% | Not comparable |
| AA Agentic IndexSource | — | 20.7% | Not comparable |
| GDPval-AASource | — | 23.9% | Not comparable |
| GDPval-AASource | — | 978 | Not comparable |
Coding3 benchmarks
Reasoning3 benchmarks
KnowledgeQwen3.5-122B-A10B wins11 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Thinking | Qwen3.5-122B-A10B | Result |
|---|---|---|---|
| MMLU-ReduxSource | 86.2% | — | Not comparable |
| GPQASource | 57.6% | 86.6% | Qwen3.5-122B-A10B leads |
| GPQA-DSource | 57.6% | — | Not comparable |
| MMLU-ProSource | — | 86.7% | Not comparable |
| SuperGPQASource | — | 67.1% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 32.3% | Not comparable |
| AA-GPQA DiamondSource | — | 85.7% | Not comparable |
| AA-HLESource | — | 23.4% | Not comparable |
| AA-Omniscience IndexSource | — | -39.6% | Not comparable |
| AA-Omniscience AccuracySource | — | 24.7% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 85.5% | Not comparable |
Multilingual1 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Thinking | Qwen3.5-122B-A10B | Result |
|---|---|---|---|
| MMLU-ProXSource | — | 82.2% | Not comparable |
Multimodal6 benchmarks
Frequently Asked Questions (3)
Which is better, Mellum2-12B-A2.5B-Thinking or Qwen3.5-122B-A10B?
Mellum2-12B-A2.5B-Thinking and Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 83.6 versus 57.6. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for instruction following, Mellum2-12B-A2.5B-Thinking or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B has the edge for instruction following in this comparison, averaging 93.4 versus 76.5. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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