Model comparison
Kimi K2.5 (Reasoning) vs Mellum2-12B-A2.5B-Instruct
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: Kimi K2.5 (Reasoning) #57 (Estimated); Mellum2-12B-A2.5B-Instruct unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.5 (Reasoning) and Mellum2-12B-A2.5B-Instruct share 1 comparable benchmark result. 1 of 8 categories are comparable. 26 results are unique to Kimi K2.5 (Reasoning); 4 to Mellum2-12B-A2.5B-Instruct.
Updated July 23, 2026- Shared results
- 1
- Kimi K2.5 (Reasoning) only
- 26
- Mellum2-12B-A2.5B-Instruct only
- 4
- Comparable categories
- 1 / 8
Treat this as a split decision. Kimi K2.5 (Reasoning) makes more sense if knowledge is the priority or you want the stronger reasoning-first profile; Mellum2-12B-A2.5B-Instruct is the better fit if you would rather avoid the extra latency and token burn of a reasoning model.
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
Kimi K2.5 (Reasoning) and Mellum2-12B-A2.5B-Instruct 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.
Kimi K2.5 (Reasoning) 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.
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 | Kimi K2.5 (Reasoning) | Δ | Mellum2-12B-A2.5B-Instruct |
|---|---|---|---|
| Knowledge | Kimi K2.5 (Reasoning)87.2 | Margin← 46.3 | Mellum2-12B-A2.5B-Instruct40.9 |
| Agentic | Kimi K2.5 (Reasoning)55.0 | MarginNo overlap | Mellum2-12B-A2.5B-InstructNot measured |
| Coding | Kimi K2.5 (Reasoning)76.8 | MarginNo overlap | Mellum2-12B-A2.5B-InstructNot measured |
| Multimodal | Kimi K2.5 (Reasoning)78.5 | MarginNo overlap | Mellum2-12B-A2.5B-InstructNot measured |
| Inst. Following | Kimi K2.5 (Reasoning)Not measured | MarginNo overlap | Mellum2-12B-A2.5B-Instruct75.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 87.6%B 40.9%Winner: Kimi K2.5 (Reasoning)Δ 46.7GPQA: Kimi K2.5 (Reasoning) scored 87.6%; Mellum2-12B-A2.5B-Instruct scored 40.9%. Kimi K2.5 (Reasoning) wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Kimi K2.5 (Reasoning) | Mellum2-12B-A2.5B-Instruct | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.5 (Reasoning)$0.6 input / $3 output | Mellum2-12B-A2.5B-InstructNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Kimi K2.5 (Reasoning)Not available | Mellum2-12B-A2.5B-InstructNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.5 (Reasoning)Not available | Mellum2-12B-A2.5B-InstructNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.5 (Reasoning)128K | Mellum2-12B-A2.5B-Instruct128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic9 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Mellum2-12B-A2.5B-Instruct | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 50.8% | — | Not comparable |
| BrowseCompSource | 60.6% | — | Not comparable |
| APEX-Agents-AASource | 11.5% | — | Not comparable |
| τ²-bench resultsSource | 95.9% | — | Not comparable |
| Gert LabsSource | 32.58% | — | Not comparable |
| AA Agentic IndexSource | 21.7% | — | Not comparable |
| GDPval-AASource | 25.4% | — | Not comparable |
| GDPval-AASource | 1009 | — | Not comparable |
| BFCL v4Source | — | 44.2% | Not comparable |
Coding4 benchmarks
Reasoning2 benchmarks
KnowledgeKimi K2.5 (Reasoning) wins10 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Mellum2-12B-A2.5B-Instruct | Result |
|---|---|---|---|
| GPQASource | 87.6% | 40.9% | Kimi K2.5 (Reasoning) leads |
| MMLU-ProSource | 87.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 35.4% | — | Not comparable |
| AA-GPQA DiamondSource | 87.9% | — | Not comparable |
| AA-HLESource | 29.4% | — | Not comparable |
| AA-Omniscience IndexSource | -8.1% | — | Not comparable |
| AA-Omniscience AccuracySource | 34.3% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 64.6% | — | Not comparable |
| MMLU-ReduxSource | — | 78.1% | Not comparable |
| GPQA-DSource | — | 40.9% | Not comparable |
Math1 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Mellum2-12B-A2.5B-Instruct | Result |
|---|---|---|---|
| AIME 2025Source | 96.1% | — | Not comparable |
Multimodal3 benchmarks
Frequently Asked Questions (2)
Which is better, Kimi K2.5 (Reasoning) or Mellum2-12B-A2.5B-Instruct?
Kimi K2.5 (Reasoning) and Mellum2-12B-A2.5B-Instruct 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, Kimi K2.5 (Reasoning) or Mellum2-12B-A2.5B-Instruct?
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.2 versus 40.9. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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