Model comparison
DeepSeek V3.2 (Thinking) vs Gemini 3.1 Pro
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3.2 (Thinking) #65 (Estimated); Gemini 3.1 Pro #83 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 (Thinking) and Gemini 3.1 Pro share 2 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to DeepSeek V3.2 (Thinking); 45 to Gemini 3.1 Pro.
Updated July 20, 2026- Shared results
- 2
- DeepSeek V3.2 (Thinking) only
- 0
- Gemini 3.1 Pro only
- 45
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek V3.2 (Thinking) and Gemini 3.1 Pro is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Gemini 3.1 Pro is priced at $2.00 input / $12.00 output per 1M tokens, versus $0.55 input / $2.19 output per 1M tokens for DeepSeek V3.2 (Thinking). Gemini 3.1 Pro has the larger context window at 1M, compared with 128K for DeepSeek V3.2 (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 V3.2 (Thinking) | Δ | Gemini 3.1 Pro |
|---|---|---|---|
| Reasoning | DeepSeek V3.2 (Thinking)Not measured | MarginNo overlap | Gemini 3.1 Pro77.1 |
| Math | DeepSeek V3.2 (Thinking)Not measured | MarginNo overlap | Gemini 3.1 Pro31.8 |
| Multimodal | DeepSeek V3.2 (Thinking)Not measured | MarginNo overlap | Gemini 3.1 Pro82.6 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.2 (Thinking) | Gemini 3.1 Pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2 (Thinking)$0.55 input / $2.19 output | Gemini 3.1 Pro$2 input / $12 output | DeepSeek V3.2 (Thinking) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V3.2 (Thinking)Not available | Gemini 3.1 Pro109 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3.2 (Thinking)Not available | Gemini 3.1 Pro29.71 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3.2 (Thinking)128K | Gemini 3.1 Pro1M | Gemini 3.1 Pro lists the larger context window. |
Benchmark Deep Dive
Agentic16 benchmarks
| Benchmark | DeepSeek V3.2 (Thinking) | Gemini 3.1 Pro | Result |
|---|---|---|---|
| Claw-EvalSource | — | 57.8% | Not comparable |
| DeepSearchQASource | — | 69.7% | Not comparable |
| τ²-bench resultsSource | — | 95.6% | Not comparable |
| AA Agentic IndexSource | — | 21.4% | Not comparable |
| APEX-Agents-AASource | — | 32.0% | Not comparable |
| GDPval-AASource | — | 23.2% | Not comparable |
| GDPval-AASource | — | 965 | Not comparable |
| Gert LabsSource | — | 56.87% | Not comparable |
| ResearchClawBenchSource | — | 13.3% | Not comparable |
| AA AutomationBenchSource | — | 37.5% | Not comparable |
| AA EnterpriseOps-GymSource | — | 42.2% | Not comparable |
| AA Harvey LABSource | — | 0.0% | Not comparable |
| AA ITBenchSource | — | 30.3% | Not comparable |
| AA Tau3 BankingSource | — | 16.5% | Not comparable |
| terminalBenchHardSource | — | 53.8% | Not comparable |
| aaTerminalBench21Source | — | 73.8% | Not comparable |
Coding5 benchmarks
Reasoning3 benchmarks
Knowledge10 benchmarks
| Benchmark | DeepSeek V3.2 (Thinking) | Gemini 3.1 Pro | Result |
|---|---|---|---|
| GPQA-DSource | — | 94.3% | Not comparable |
| HLE w/o toolsSource | — | 45.4% | Not comparable |
| HealthBench HardSource | — | 20.6% | Not comparable |
| MedXpertQA (Text)Source | — | 71.5% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 46.5% | Not comparable |
| AA-GPQA DiamondSource | — | 94.1% | Not comparable |
| AA-HLESource | — | 44.7% | Not comparable |
| AA-Omniscience IndexSource | — | 32.9% | Not comparable |
| AA-Omniscience AccuracySource | — | 55.3% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 49.9% | Not comparable |
Math2 benchmarks
Multilingual1 benchmarks
| Benchmark | DeepSeek V3.2 (Thinking) | Gemini 3.1 Pro | Result |
|---|---|---|---|
| AA Global-MMLU-LiteSource | — | 93.2% | Not comparable |
Multimodal9 benchmarks
| Benchmark | DeepSeek V3.2 (Thinking) | Gemini 3.1 Pro | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1206 | 1284 | Gemini 3.1 Pro leads |
| MMMU-ProSource | — | 83.9% | Not comparable |
| CharXivSource | — | 80.2% | Not comparable |
| ERQASource | — | 69.4% | Not comparable |
| SimpleVQASource | — | 72.4% | Not comparable |
| ScreenSpot ProSource | — | 84.4% | Not comparable |
| ZeroBenchSource | — | 29.0% | Not comparable |
| MedXpertQA (MM)Source | — | 81.3% | Not comparable |
| AA-MMMU-ProSource | — | 82.4% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V3.2 (Thinking) | Gemini 3.1 Pro | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 77.1% | Not comparable |
Frequently Asked Questions (3)
Can I compare DeepSeek V3.2 (Thinking) and Gemini 3.1 Pro on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for DeepSeek V3.2 (Thinking) and Gemini 3.1 Pro today?
DeepSeek V3.2 (Thinking): $0.55 input / $2.19 output per 1M tokens Gemini 3.1 Pro: $2.00 input / $12.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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