Model comparison
DeepSeek V4 Flash Base 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.
Evidence parity. DeepSeek V4 Flash Base and Mellum2-12B-A2.5B-Thinking share 1 comparable benchmark result. 1 of 8 categories are comparable. 23 results are unique to DeepSeek V4 Flash Base; 4 to Mellum2-12B-A2.5B-Thinking.
Updated July 23, 2026- Shared results
- 1
- DeepSeek V4 Flash Base only
- 23
- Mellum2-12B-A2.5B-Thinking only
- 4
- Comparable categories
- 1 / 8
Treat this as a split decision. DeepSeek V4 Flash Base 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
DeepSeek V4 Flash Base 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 DeepSeek V4 Flash Base 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. DeepSeek V4 Flash Base 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 | DeepSeek V4 Flash Base | Δ | Mellum2-12B-A2.5B-Thinking |
|---|---|---|---|
| Knowledge | DeepSeek V4 Flash Base56.4 | Margin→ 1.2 | Mellum2-12B-A2.5B-Thinking57.6 |
| Reasoning | DeepSeek V4 Flash Base44.7 | MarginNo overlap | Mellum2-12B-A2.5B-ThinkingNot measured |
| Inst. Following | DeepSeek V4 Flash BaseNot measured | MarginNo overlap | Mellum2-12B-A2.5B-Thinking76.5 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Flash Base | Mellum2-12B-A2.5B-Thinking | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash BaseNot available | Mellum2-12B-A2.5B-ThinkingNot available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V4 Flash BaseNot available | Mellum2-12B-A2.5B-ThinkingNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Flash BaseNot available | Mellum2-12B-A2.5B-ThinkingNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash Base1M | Mellum2-12B-A2.5B-Thinking128K | DeepSeek V4 Flash Base lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | DeepSeek V4 Flash Base | Mellum2-12B-A2.5B-Thinking | Result |
|---|---|---|---|
| BFCL v4Source | — | 45.6% | Not comparable |
Coding2 benchmarks
Reasoning6 benchmarks
KnowledgeMellum2-12B-A2.5B-Thinking wins14 benchmarks
| Benchmark | DeepSeek V4 Flash Base | Mellum2-12B-A2.5B-Thinking | Result |
|---|---|---|---|
| AGIEvalSource | 82.6% | — | Not comparable |
| MMLUSource | 88.7% | — | Not comparable |
| MMLU-ReduxSource | 89.4% | 86.2% | DeepSeek V4 Flash Base leads |
| MMLU-ProSource | 68.3% | — | Not comparable |
| MMMLUSource | 88.8% | — | Not comparable |
| C-EvalSource | 92.1% | — | Not comparable |
| CMMLUSource | 90.4% | — | Not comparable |
| MultiLoKoSource | 42.2% | — | Not comparable |
| SimpleQASource | 30.1% | — | Not comparable |
| SuperGPQASource | 46.5% | — | Not comparable |
| FACTS ParametricSource | 33.9% | — | Not comparable |
| TriviaQASource | 82.8% | — | Not comparable |
| GPQASource | — | 57.6% | Not comparable |
| GPQA-DSource | — | 57.6% | Not comparable |
Math3 benchmarks
Multilingual1 benchmarks
| Benchmark | DeepSeek V4 Flash Base | Mellum2-12B-A2.5B-Thinking | Result |
|---|---|---|---|
| MGSMSource | 85.7% | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Flash Base | Mellum2-12B-A2.5B-Thinking | Result |
|---|---|---|---|
| IFEvalSource | — | 76.5% | Not comparable |
Frequently Asked Questions (2)
Which is better, DeepSeek V4 Flash Base or Mellum2-12B-A2.5B-Thinking?
DeepSeek V4 Flash Base 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, DeepSeek V4 Flash Base or Mellum2-12B-A2.5B-Thinking?
Mellum2-12B-A2.5B-Thinking has the edge for knowledge tasks in this comparison, averaging 57.6 versus 56.4. Inside this category, MMLU-Redux is the benchmark that creates the most daylight between them.
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