Model comparison
DeepSeek-V3.1 vs Gemini 3.1 Flash Lite
DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 40.8 on the Noometry Index.
Last verified . 24 shared benchmarks.
Summary
- They share 24 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 4 categories and Gemini 3.1 Flash Lite in 4 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in long context, where Gemini 3.1 Flash Lite leads 42.5 to 36.3.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 53.2% for DeepSeek-V3.1 and 67.2% for Gemini 3.1 Flash Lite.
- DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $0.25 / $1.50 for Gemini 3.1 Flash Lite.
- Gemini 3.1 Flash Lite accepts more context: 1.05M tokens versus 164K.
- DeepSeek-V3.1 has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1 | Gemini 3.1 Flash Lite | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 42.8 | 40.8 |
| Released | 2025-08-21 | 2026-03-03 |
| Weights | Open | Proprietary |
| Context window | 164K | 1.05M |
| Max output | 8K | 66K |
| Input $ / M tokens | $0.25 | $0.25 |
| Output $ / M tokens | $0.95 | $1.50 |
| Results tracked | 27 | 38 |
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Category by category
Coding DeepSeek-V3.1 leads
DeepSeek-V3.1: 40.3 (#144), Gemini 3.1 Flash Lite: 37.8 (#188)
| Benchmark | DeepSeek-V3.1 | Gemini 3.1 Flash Lite |
|---|---|---|
| WeirdML | 38.4% | 52.2% |
| LMArena Coding | 1417 | 1400 |
| LMArena WebDev | — | 1256 |
| SciCode | — | 41.9% |
| ALE-Bench | — | 797.73 |
Agentic & Tool Use Not comparable
DeepSeek-V3.1: —, Gemini 3.1 Flash Lite: 30.2 (#79)
| Benchmark | DeepSeek-V3.1 | Gemini 3.1 Flash Lite |
|---|---|---|
| DeepResearch Bench | — | 37.3% |
Reasoning DeepSeek-V3.1 leads
DeepSeek-V3.1: 27.9 (#110), Gemini 3.1 Flash Lite: 22.9 (#186)
| Benchmark | DeepSeek-V3.1 | Gemini 3.1 Flash Lite |
|---|---|---|
| Kagi LLM Benchmark | 53.2% | 67.2% |
| LMArena Hard Prompts | 1417 | 1407 |
| DTBench | 82.7% | 76.8% |
| LMCA | 24.3% | 35% |
| Epoch Capabilities Index | 139.92 | 144.47 |
| ForecastBench | 58 | 54.4 |
| SimpleBench | 40% | — |
| NYT Connections (extended) | — | 8.2% |
| CritPt | — | 1.1% |
| Chess Puzzles | — | 25% |
| EnigmaEval | — | 3% |
| Thematic Generalization | — | 63.3% |
Math Gemini 3.1 Flash Lite leads
DeepSeek-V3.1: 38.9 (#122), Gemini 3.1 Flash Lite: 40.7 (#90)
| Benchmark | DeepSeek-V3.1 | Gemini 3.1 Flash Lite |
|---|---|---|
| LMArena Math | 1420 | 1428 |
| FrontierMath (Tiers 1-3) | — | 27.7% |
| OTIS Mock AIME 2024-2025 | — | 80% |
Knowledge DeepSeek-V3.1 leads
DeepSeek-V3.1: 43.7 (#90), Gemini 3.1 Flash Lite: 41.9 (#104)
| Benchmark | DeepSeek-V3.1 | Gemini 3.1 Flash Lite |
|---|---|---|
| Vectara Hallucination Rate | 5.5% | 8.2% |
| LMArena Expert | 1405 | 1398 |
| GPQA Diamond | — | 81.8% |
| Humanity's Last Exam | — | 8.6% |
Multimodal Not comparable
DeepSeek-V3.1: —, Gemini 3.1 Flash Lite: 39.4 (#60)
| Benchmark | DeepSeek-V3.1 | Gemini 3.1 Flash Lite |
|---|---|---|
| LMArena Vision | — | 1240 |
Multilingual Too close to call
DeepSeek-V3.1: 51.6 (#106), Gemini 3.1 Flash Lite: 52.3 (#86)
| Benchmark | DeepSeek-V3.1 | Gemini 3.1 Flash Lite |
|---|---|---|
| LMArena Non-English | 1400 | 1411 |
| LMArena Chinese | 1469 | 1461 |
| LMArena French | 1447 | 1424 |
| LMArena German | 1411 | 1429 |
| LMArena Japanese | 1378 | 1413 |
| LMArena Korean | 1337 | 1392 |
| LMArena Russian | 1405 | 1420 |
| LMArena Spanish | 1431 | 1421 |
Instruction Following DeepSeek-V3.1 leads
DeepSeek-V3.1: 73.9 (#110), Gemini 3.1 Flash Lite: 72.7 (#131)
| Benchmark | DeepSeek-V3.1 | Gemini 3.1 Flash Lite |
|---|---|---|
| LMArena Instruction Following | 1400 | 1377 |
Long Context Gemini 3.1 Flash Lite leads
DeepSeek-V3.1: 36.3 (#232), Gemini 3.1 Flash Lite: 42.5 (#122)
| Benchmark | DeepSeek-V3.1 | Gemini 3.1 Flash Lite |
|---|---|---|
| LMArena Longer Query | 1422 | 1394 |
| Fiction.LiveBench | 52.8% | — |
Writing & Preference Too close to call
DeepSeek-V3.1: 60.3 (#98), Gemini 3.1 Flash Lite: 60.9 (#94)
| Benchmark | DeepSeek-V3.1 | Gemini 3.1 Flash Lite |
|---|---|---|
| LMArena Text | 1420 | 1416 |
| LMArena Creative Writing | 1401 | 1401 |
| LMArena Multi-Turn | 1408 | 1417 |
| EQ-Bench Creative Writing | 1436 | — |
Frequently asked questions
Is DeepSeek-V3.1 better than Gemini 3.1 Flash Lite?
DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 40.8 on the Noometry Index.
Which is cheaper, DeepSeek-V3.1 or Gemini 3.1 Flash Lite?
DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; Gemini 3.1 Flash Lite lists at $0.25 and $1.50.
Is DeepSeek-V3.1 or Gemini 3.1 Flash Lite better for coding?
DeepSeek-V3.1 scores higher on coding benchmarks: 40.3 versus 37.8 in the Noometry coding category.
Which has the bigger context window?
Gemini 3.1 Flash Lite does, with 1.05M tokens against 164K.
How many benchmarks do DeepSeek-V3.1 and Gemini 3.1 Flash Lite share?
24 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Gemini 3.1 Flash Lite has 38.