Model comparison
DeepSeek V4 Pro vs Gemma 4 31B
Head-to-head evidence from 4 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro #46 (Supported); Gemma 4 31B #43 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro and Gemma 4 31B share 4 comparable benchmark results. 2 of 8 categories are comparable. 19 results are unique to DeepSeek V4 Pro; 25 to Gemma 4 31B.
Updated July 23, 2026- Shared results
- 4
- DeepSeek V4 Pro only
- 19
- Gemma 4 31B only
- 25
- Comparable categories
- 2 / 8
Pick Gemma 4 31B if you want the stronger benchmark profile. DeepSeek V4 Pro only becomes the better choice if coding is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 4 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
Gemma 4 31B has the cleaner BenchAlign overall profile here, landing at 61.08 versus 60.66. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Gemma 4 31B's sharpest advantage is in knowledge, where it averages 52.9 against 41.3. The single biggest benchmark swing on the page is HLE, 7.7% to 26.5%. DeepSeek V4 Pro does hit back in coding, so the answer changes if that is the part of the workload you care about most.
DeepSeek V4 Pro is also the more expensive model on tokens at $0.43 input / $0.87 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 31B. That is roughly Infinityx on output cost alone. Gemma 4 31B is the reasoning model in the pair, while DeepSeek V4 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. DeepSeek V4 Pro gives you the larger context window at 1M, compared with 256K for Gemma 4 31B.
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 Pro | Δ | Gemma 4 31B |
|---|---|---|---|
| Coding | DeepSeek V4 Pro65.3 | Margin← 23.7 | Gemma 4 31B41.6 |
| Knowledge | DeepSeek V4 Pro41.3 | Margin→ 11.6 | Gemma 4 31B52.9 |
| Agentic | DeepSeek V4 Pro59.1 | MarginNo overlap | Gemma 4 31BNot measured |
| Math | DeepSeek V4 Pro31.7 | MarginNo overlap | Gemma 4 31BNot measured |
| Multimodal | DeepSeek V4 ProNot measured | MarginNo overlap | Gemma 4 31B76.9 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 7.7%B 26.5%Winner: Gemma 4 31BΔ 18.8HLE: DeepSeek V4 Pro scored 7.7%; Gemma 4 31B scored 26.5%. Gemma 4 31B wins this benchmark. - Source ↗
GPQA
KnowledgeA 72.9%B 84.3%Winner: Gemma 4 31BΔ 11.4GPQA: DeepSeek V4 Pro scored 72.9%; Gemma 4 31B scored 84.3%. Gemma 4 31B wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 82.9%B 85.2%Winner: Gemma 4 31BΔ 2.3MMLU-Pro: DeepSeek V4 Pro scored 82.9%; Gemma 4 31B scored 85.2%. Gemma 4 31B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro | Gemma 4 31B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro$0.435 input / $0.87 output | Gemma 4 31B$0 input / $0 output | Gemma 4 31B has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 ProNot available | Gemma 4 31BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 ProNot available | Gemma 4 31BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro1M | Gemma 4 31B256K | DeepSeek V4 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic14 benchmarks
| Benchmark | DeepSeek V4 Pro | Gemma 4 31B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.1% | — | Not comparable |
| MCP AtlasSource | 69.4% | — | Not comparable |
| ToolathlonSource | 46.3% | — | Not comparable |
| Claw-EvalSource | 59.8% | — | Not comparable |
| Gert LabsSource | 50.28% | 35.26% | DeepSeek V4 Pro leads |
| ResearchClawBenchSource | 17.1% | — | Not comparable |
| AA Agentic IndexSource | — | 14.4% | Not comparable |
| τ²-bench resultsSource | — | 59.9% | Not comparable |
| GDPval-AASource | — | 15.2% | Not comparable |
| GDPval-AASource | — | 804 | Not comparable |
| AA EnterpriseOps-GymSource | — | 28.3% | Not comparable |
| AA ITBenchSource | — | 37.3% | Not comparable |
| AA Tau3 BankingSource | — | 15.1% | Not comparable |
| terminalBenchHardSource | — | 36.4% | Not comparable |
CodingDeepSeek V4 Pro wins8 benchmarks
| Benchmark | DeepSeek V4 Pro | Gemma 4 31B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.6% | — | Not comparable |
| SWE-bench ProSource | 52.1% | — | Not comparable |
| SWE MultilingualSource | 69.8% | — | Not comparable |
| Terminal-Bench 2.0Source | 59.1% | — | Not comparable |
| SWE-RebenchSource | — | 41.6% | Not comparable |
| React Native EvalsSource | — | 75.2% | Not comparable |
| AA Coding IndexSource | — | 43.4% | Not comparable |
| AA-SciCodeSource | — | 43.4% | Not comparable |
Reasoning4 benchmarks
KnowledgeGemma 4 31B wins14 benchmarks
| Benchmark | DeepSeek V4 Pro | Gemma 4 31B | Result |
|---|---|---|---|
| MMLU-ProSource | 82.9% | 85.2% | Gemma 4 31B leads |
| SimpleQASource | 45% | — | Not comparable |
| Chinese-SimpleQASource | 75.8% | — | Not comparable |
| GPQASource | 72.9% | 84.3% | Gemma 4 31B leads |
| GPQA-DSource | 72.9% | — | Not comparable |
| HLESource | 7.7% | 26.5% | Gemma 4 31B leads |
| HLE w/o toolsSource | — | 19.5% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 29.4% | Not comparable |
| AA-GPQA DiamondSource | — | 85.7% | Not comparable |
| AA-HLESource | — | 22.7% | Not comparable |
| AA-Omniscience IndexSource | — | -45.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 19.9% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 81.6% | Not comparable |
| AA Openness IndexSource | — | 38.9% | Not comparable |
Math4 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro | Gemma 4 31B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 75.6% | Not comparable |
Frequently Asked Questions (3)
Which is better, DeepSeek V4 Pro or Gemma 4 31B?
Gemma 4 31B is ahead on BenchLM's BenchAlign leaderboard, 61.08 to 60.66. The biggest single separator in this matchup is HLE, where the scores are 7.7% and 26.5%.
Which is better for knowledge tasks, DeepSeek V4 Pro or Gemma 4 31B?
Gemma 4 31B has the edge for knowledge tasks in this comparison, averaging 52.9 versus 41.3. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Pro or Gemma 4 31B?
DeepSeek V4 Pro has the edge for coding in this comparison, averaging 65.3 versus 41.6. Gemma 4 31B stays close enough that the answer can still flip depending on your workload.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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