Model comparison
Mellum2-12B-A2.5B-Instruct vs Qwen3.6 Plus
Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Mellum2-12B-A2.5B-Instruct unranked (Not scored); Qwen3.6 Plus #30 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Mellum2-12B-A2.5B-Instruct and Qwen3.6 Plus share 3 comparable benchmark results. 2 of 8 categories are comparable. 2 results are unique to Mellum2-12B-A2.5B-Instruct; 57 to Qwen3.6 Plus.
Updated July 23, 2026- Shared results
- 3
- Mellum2-12B-A2.5B-Instruct only
- 2
- Qwen3.6 Plus only
- 57
- Comparable categories
- 2 / 8
Treat this as a split decision. Mellum2-12B-A2.5B-Instruct makes more sense if you would rather avoid the extra latency and token burn of a reasoning model; Qwen3.6 Plus is the better fit if knowledge is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 3 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-Instruct and Qwen3.6 Plus 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 Plus is the reasoning model in the pair, while Mellum2-12B-A2.5B-Instruct 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. Qwen3.6 Plus gives you the larger context window at 1M, compared with 128K for Mellum2-12B-A2.5B-Instruct.
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-Instruct | Δ | Qwen3.6 Plus |
|---|---|---|---|
| Knowledge | Mellum2-12B-A2.5B-Instruct40.9 | Margin→ 16.2 | Qwen3.6 Plus57.1 |
| Inst. Following | Mellum2-12B-A2.5B-Instruct75.8 | Margin→ 6.5 | Qwen3.6 Plus82.3 |
| Agentic | Mellum2-12B-A2.5B-InstructNot measured | MarginNo overlap | Qwen3.6 Plus61.6 |
| Coding | Mellum2-12B-A2.5B-InstructNot measured | MarginNo overlap | Qwen3.6 Plus70.3 |
| Reasoning | Mellum2-12B-A2.5B-InstructNot measured | MarginNo overlap | Qwen3.6 Plus62.0 |
| Math | Mellum2-12B-A2.5B-InstructNot measured | MarginNo overlap | Qwen3.6 Plus60.5 |
| Multilingual | Mellum2-12B-A2.5B-InstructNot measured | MarginNo overlap | Qwen3.6 Plus84.7 |
| Multimodal | Mellum2-12B-A2.5B-InstructNot measured | MarginNo overlap | Qwen3.6 Plus79.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 40.9%B 90.4%Winner: Qwen3.6 PlusΔ 49.5GPQA: Mellum2-12B-A2.5B-Instruct scored 40.9%; Qwen3.6 Plus scored 90.4%. Qwen3.6 Plus wins this benchmark. - Source ↗
IFEval
Inst. FollowingA 75.8%B 94.3%Winner: Qwen3.6 PlusΔ 18.5IFEval: Mellum2-12B-A2.5B-Instruct scored 75.8%; Qwen3.6 Plus scored 94.3%. Qwen3.6 Plus 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-Instruct | Qwen3.6 Plus | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Mellum2-12B-A2.5B-InstructNot available | Qwen3.6 PlusNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Mellum2-12B-A2.5B-InstructNot available | Qwen3.6 PlusNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Mellum2-12B-A2.5B-InstructNot available | Qwen3.6 PlusNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Mellum2-12B-A2.5B-Instruct128K | Qwen3.6 Plus1M | Qwen3.6 Plus lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Instruct | Qwen3.6 Plus | Result |
|---|---|---|---|
| BFCL v4Source | 44.2% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 61.6% | Not comparable |
| Claw-EvalSource | — | 58.8% | Not comparable |
| QwenClawBenchSource | — | 57.2% | Not comparable |
| τ³-bench resultsSource | — | 70.7% | Not comparable |
| VITA-BenchSource | — | 44.3% | Not comparable |
| DeepPlanningSource | — | 41.5% | Not comparable |
| ToolathlonSource | — | 39.8% | Not comparable |
| MCP AtlasSource | — | 48.2% | Not comparable |
| MCP-TasksSource | — | 74.1% | Not comparable |
| WideResearchSource | — | 74.3% | Not comparable |
| AA Agentic IndexSource | — | 27.6% | Not comparable |
| τ²-bench resultsSource | — | 97.7% | Not comparable |
| GDPval-AASource | — | 31.8% | Not comparable |
| GDPval-AASource | — | 1135 | Not comparable |
| Gert LabsSource | — | 50.60% | Not comparable |
| ResearchClawBenchSource | — | 18.0% | Not comparable |
Coding7 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Instruct | Qwen3.6 Plus | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | — | 78.8% | Not comparable |
| SWE-bench ProSource | — | 56.6% | Not comparable |
| SWE MultilingualSource | — | 73.8% | Not comparable |
| LiveCodeBench v6Source | — | 87.1% | Not comparable |
| Vibe Code BenchSource | — | 25.56% | Not comparable |
| AA Coding IndexSource | — | 54.5% | Not comparable |
| AA-SciCodeSource | — | 40.7% | Not comparable |
Reasoning4 benchmarks
KnowledgeQwen3.6 Plus wins13 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Instruct | Qwen3.6 Plus | Result |
|---|---|---|---|
| MMLU-ReduxSource | 78.1% | 94.5% | Qwen3.6 Plus leads |
| GPQASource | 40.9% | 90.4% | Qwen3.6 Plus leads |
| GPQA-DSource | 40.9% | — | Not comparable |
| SuperGPQASource | — | 71.6% | Not comparable |
| MMLU-ProSource | — | 88.5% | Not comparable |
| C-EvalSource | — | 93.3% | Not comparable |
| HLESource | — | 28.8% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 39.6% | Not comparable |
| AA-GPQA DiamondSource | — | 88.2% | Not comparable |
| AA-HLESource | — | 25.7% | Not comparable |
| AA-Omniscience IndexSource | — | 2.7% | Not comparable |
| AA-Omniscience AccuracySource | — | 26.2% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 32.0% | Not comparable |
Math7 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Instruct | Qwen3.6 Plus | Result |
|---|---|---|---|
| AIME26Source | — | 95.3% | Not comparable |
| HMMT Feb 2025Source | — | 96.7% | Not comparable |
| HMMT Nov 2025Source | — | 94.6% | Not comparable |
| HMMT Feb 2026Source | — | 87.8% | Not comparable |
| MMAnswerBenchSource | — | 83.8% | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | — | 26.207% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 8.333% | Not comparable |
Multilingual2 benchmarks
Multimodal9 benchmarks
| Benchmark | Mellum2-12B-A2.5B-Instruct | Qwen3.6 Plus | Result |
|---|---|---|---|
| MMMUSource | — | 86.0% | Not comparable |
| MMMU-ProSource | — | 78.8% | Not comparable |
| MathVisionSource | — | 88.0% | Not comparable |
| VideoMMMUSource | — | 84.0% | Not comparable |
| ScreenSpot ProSource | — | 68.2% | Not comparable |
| CharXivSource | — | 81.5% | Not comparable |
| V*Source | — | 96.9% | Not comparable |
| AA-MMMU-ProSource | — | 78.0% | Not comparable |
| Design Arena WebsiteSource | — | 1249 | Not comparable |
Frequently Asked Questions (3)
Which is better, Mellum2-12B-A2.5B-Instruct or Qwen3.6 Plus?
Mellum2-12B-A2.5B-Instruct and Qwen3.6 Plus 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-Instruct or Qwen3.6 Plus?
Qwen3.6 Plus has the edge for knowledge tasks in this comparison, averaging 57.1 versus 40.9. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for instruction following, Mellum2-12B-A2.5B-Instruct or Qwen3.6 Plus?
Qwen3.6 Plus has the edge for instruction following in this comparison, averaging 82.3 versus 75.8. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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