Model comparison
Gemini 2.5 Pro vs Mellum2-12B-A2.5B-Thinking
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: Gemini 2.5 Pro #70 (Supported); Mellum2-12B-A2.5B-Thinking unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Gemini 2.5 Pro and Mellum2-12B-A2.5B-Thinking share 1 comparable benchmark result. 1 of 8 categories are comparable. 23 results are unique to Gemini 2.5 Pro; 4 to Mellum2-12B-A2.5B-Thinking.
Updated July 23, 2026- Shared results
- 1
- Gemini 2.5 Pro only
- 23
- Mellum2-12B-A2.5B-Thinking only
- 4
- Comparable categories
- 1 / 8
Treat this as a split decision. Gemini 2.5 Pro makes more sense if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model; Mellum2-12B-A2.5B-Thinking is the better fit if knowledge is the priority or you want the stronger reasoning-first profile.
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
Gemini 2.5 Pro and Mellum2-12B-A2.5B-Thinking 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.
Mellum2-12B-A2.5B-Thinking is the reasoning model in the pair, while Gemini 2.5 Pro 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. Gemini 2.5 Pro gives you the larger context window at 1M, 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 | Gemini 2.5 Pro | Δ | Mellum2-12B-A2.5B-Thinking |
|---|---|---|---|
| Knowledge | Gemini 2.5 Pro27.4 | Margin→ 30.2 | Mellum2-12B-A2.5B-Thinking57.6 |
| Coding | Gemini 2.5 Pro63.8 | MarginNo overlap | Mellum2-12B-A2.5B-ThinkingNot measured |
| Math | Gemini 2.5 Pro11.6 | MarginNo overlap | Mellum2-12B-A2.5B-ThinkingNot measured |
| Inst. Following | Gemini 2.5 ProNot measured | MarginNo overlap | Mellum2-12B-A2.5B-Thinking76.5 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 83%B 57.6%Winner: Gemini 2.5 ProΔ 25.4GPQA: Gemini 2.5 Pro scored 83%; Mellum2-12B-A2.5B-Thinking scored 57.6%. Gemini 2.5 Pro wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Gemini 2.5 Pro | Mellum2-12B-A2.5B-Thinking | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Gemini 2.5 Pro$1.25 input / $10 output | Mellum2-12B-A2.5B-ThinkingNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Gemini 2.5 Pro117 tok/s | Mellum2-12B-A2.5B-ThinkingNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Gemini 2.5 Pro21.19 s | Mellum2-12B-A2.5B-ThinkingNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Gemini 2.5 Pro1M | Mellum2-12B-A2.5B-Thinking128K | Gemini 2.5 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic6 benchmarks
Coding4 benchmarks
Reasoning2 benchmarks
KnowledgeMellum2-12B-A2.5B-Thinking wins10 benchmarks
| Benchmark | Gemini 2.5 Pro | Mellum2-12B-A2.5B-Thinking | Result |
|---|---|---|---|
| GPQASource | 83% | 57.6% | Gemini 2.5 Pro leads |
| HLESource | 18.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 25.8% | — | Not comparable |
| AA-GPQA DiamondSource | 84.4% | — | Not comparable |
| AA-HLESource | 21.1% | — | Not comparable |
| AA-Omniscience IndexSource | -14.3% | — | Not comparable |
| AA-Omniscience AccuracySource | 39.0% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 87.4% | — | Not comparable |
| MMLU-ReduxSource | — | 86.2% | Not comparable |
| GPQA-DSource | — | 57.6% | Not comparable |
Math2 benchmarks
Multimodal2 benchmarks
Frequently Asked Questions (2)
Which is better, Gemini 2.5 Pro or Mellum2-12B-A2.5B-Thinking?
Gemini 2.5 Pro and Mellum2-12B-A2.5B-Thinking 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, Gemini 2.5 Pro or Mellum2-12B-A2.5B-Thinking?
Mellum2-12B-A2.5B-Thinking has the edge for knowledge tasks in this comparison, averaging 57.6 versus 27.4. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Related Comparisons
Explore More
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.