Model comparison
DeepSeek V4 Flash vs Mellum2-12B-A2.5B-Thinking
Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Flash #61 (Estimated); Mellum2-12B-A2.5B-Thinking unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Flash and Mellum2-12B-A2.5B-Thinking share 2 comparable benchmark results. 1 of 8 categories are comparable. 20 results are unique to DeepSeek V4 Flash; 3 to Mellum2-12B-A2.5B-Thinking.
Updated July 23, 2026- Shared results
- 2
- DeepSeek V4 Flash only
- 20
- Mellum2-12B-A2.5B-Thinking only
- 3
- Comparable categories
- 1 / 8
Treat this as a split decision. DeepSeek V4 Flash 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 2 shared benchmark results 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 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 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 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 | Δ | Mellum2-12B-A2.5B-Thinking |
|---|---|---|---|
| Knowledge | DeepSeek V4 Flash38.8 | Margin→ 18.8 | Mellum2-12B-A2.5B-Thinking57.6 |
| Agentic | DeepSeek V4 Flash49.1 | MarginNo overlap | Mellum2-12B-A2.5B-ThinkingNot measured |
| Coding | DeepSeek V4 Flash64.2 | MarginNo overlap | Mellum2-12B-A2.5B-ThinkingNot measured |
| Math | DeepSeek V4 Flash40.8 | MarginNo overlap | Mellum2-12B-A2.5B-ThinkingNot measured |
| Inst. Following | DeepSeek V4 FlashNot 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 71.2%B 57.6%Winner: DeepSeek V4 FlashΔ 13.6GPQA: DeepSeek V4 Flash scored 71.2%; Mellum2-12B-A2.5B-Thinking scored 57.6%. DeepSeek V4 Flash wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Flash | Mellum2-12B-A2.5B-Thinking | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash$0.14 input / $0.28 output | Mellum2-12B-A2.5B-ThinkingNot available | A complete price comparison is not available. |
| Generation speedtokens per second | DeepSeek V4 FlashNot available | Mellum2-12B-A2.5B-ThinkingNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 FlashNot available | Mellum2-12B-A2.5B-ThinkingNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash1M | Mellum2-12B-A2.5B-Thinking128K | DeepSeek V4 Flash lists the larger context window. |
Benchmark Deep Dive
Agentic6 benchmarks
Coding4 benchmarks
Reasoning2 benchmarks
KnowledgeMellum2-12B-A2.5B-Thinking wins7 benchmarks
| Benchmark | DeepSeek V4 Flash | Mellum2-12B-A2.5B-Thinking | Result |
|---|---|---|---|
| MMLU-ProSource | 83% | — | Not comparable |
| SimpleQASource | 23.1% | — | Not comparable |
| Chinese-SimpleQASource | 71.5% | — | Not comparable |
| GPQASource | 71.2% | 57.6% | DeepSeek V4 Flash leads |
| GPQA-DSource | 71.2% | 57.6% | DeepSeek V4 Flash leads |
| HLESource | 8.1% | — | Not comparable |
| MMLU-ReduxSource | — | 86.2% | Not comparable |
Math4 benchmarks
Multimodal1 benchmarks
| Benchmark | DeepSeek V4 Flash | Mellum2-12B-A2.5B-Thinking | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1238 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Flash | Mellum2-12B-A2.5B-Thinking | Result |
|---|---|---|---|
| IFEvalSource | — | 76.5% | Not comparable |
Frequently Asked Questions (2)
Which is better, DeepSeek V4 Flash or Mellum2-12B-A2.5B-Thinking?
DeepSeek V4 Flash 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 or Mellum2-12B-A2.5B-Thinking?
Mellum2-12B-A2.5B-Thinking has the edge for knowledge tasks in this comparison, averaging 57.6 versus 38.8. 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.