Model comparison
DeepSeek V4 Flash vs Gemini 3.7 Flash
Gemini 3.7 Flash is the stronger model overall, scoring 59.8 to 53.6 on the Noometry Index. DeepSeek V4 Flash costs 5.7× less per token, which makes it the better buy when Gemini 3.7 Flash's lead doesn't matter for your workload.
Last verified . 37 shared benchmarks.
DeepSeek
GoogleSummary
- They share 37 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 0 categories and Gemini 3.7 Flash in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.7 Flash leads 70.0 to 53.7.
- The biggest single-benchmark swing is SimpleQA Verified: 33.6% for DeepSeek V4 Flash and 69.2% for Gemini 3.7 Flash.
- DeepSeek V4 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.75 / $3.75 for Gemini 3.7 Flash.
- Gemini 3.7 Flash accepts more context: 1.05M tokens versus 1M.
- DeepSeek V4 Flash has downloadable open weights; the other is API-only.
Side by side
| DeepSeek V4 Flash | Gemini 3.7 Flash | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 53.6 | 59.8 |
| Released | 2026-04-24 | 2026-08-13 |
| Weights | Open | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 393K | 66K |
| Input $ / M tokens | $0.15 | $0.75 |
| Output $ / M tokens | $0.60 | $3.75 |
| Results tracked | 41 | 44 |
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Category by category
Coding Gemini 3.7 Flash leads
DeepSeek V4 Flash: 47.9 (#59), Gemini 3.7 Flash: 56.2 (#22)
| Benchmark | DeepSeek V4 Flash | Gemini 3.7 Flash |
|---|---|---|
| FrontierCode | 18.8% | 43.6% |
| LMArena WebDev | 1582 | 1592 |
| SciCode | 49.9% | 59.8% |
| LMArena Coding | 1457 | 1497 |
| ALE-Bench | 1,306 | 904.3 |
| DeepSWE | — | 65.5% |
| FrontierSWE | — | 20.3% |
| WeirdML | 63% | — |
Agentic & Tool Use Not comparable
DeepSeek V4 Flash: —, Gemini 3.7 Flash: 42.1 (#19)
| Benchmark | DeepSeek V4 Flash | Gemini 3.7 Flash |
|---|---|---|
| APEX-Agents | — | 67.8% |
| Remote Labor Index | — | 5% |
| GDP.pdf | — | 23.8% |
Reasoning Gemini 3.7 Flash leads
DeepSeek V4 Flash: 53.7 (#30), Gemini 3.7 Flash: 70.0 (#15)
| Benchmark | DeepSeek V4 Flash | Gemini 3.7 Flash |
|---|---|---|
| ARC-AGI-2 | 61.4% | 84.6% |
| NYT Connections (extended) | 89.6% | 94% |
| ARC-AGI-1 | 89% | 95.5% |
| CritPt | 16.6% | 14.3% |
| Chess Puzzles | 33% | 47% |
| LMArena Hard Prompts | 1444 | 1494 |
| Mystery Game Puzzles | 34% | 37% |
| DTBench | 90.9% | 96.8% |
| LMCA | 41.7% | 50.4% |
| Epoch Capabilities Index | 154.49 | 157.27 |
| SimpleBench | 61.1% | — |
| Kagi LLM Benchmark | 52.2% | — |
Math Gemini 3.7 Flash leads
DeepSeek V4 Flash: 60.3 (#37), Gemini 3.7 Flash: 69.6 (#23)
| Benchmark | DeepSeek V4 Flash | Gemini 3.7 Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 57.5% | 71.6% |
| FrontierMath Tier 4 | 24.4% | 36.6% |
| OTIS Mock AIME 2024-2025 | 94.4% | 97.2% |
| ProofBench | 56% | 58% |
| LMArena Math | 1427 | 1507 |
| MathArena Final-Answer Competitions | 76.5% | — |
Knowledge Gemini 3.7 Flash leads
DeepSeek V4 Flash: 55.4 (#48), Gemini 3.7 Flash: 69.7 (#5)
| Benchmark | DeepSeek V4 Flash | Gemini 3.7 Flash |
|---|---|---|
| GPQA Diamond | 91% | 94.8% |
| SimpleQA Verified | 33.6% | 69.2% |
| LMArena Expert | 1441 | 1508 |
Multimodal Not comparable
DeepSeek V4 Flash: —, Gemini 3.7 Flash: 37.3 (#73)
| Benchmark | DeepSeek V4 Flash | Gemini 3.7 Flash |
|---|---|---|
| LMArena Vision | — | 1316 |
| Furniture Assembly | — | 26.7% |
Multilingual Gemini 3.7 Flash leads
DeepSeek V4 Flash: 53.0 (#72), Gemini 3.7 Flash: 57.6 (#7)
| Benchmark | DeepSeek V4 Flash | Gemini 3.7 Flash |
|---|---|---|
| LMArena Non-English | 1420 | 1484 |
| LMArena Chinese | 1468 | 1548 |
| LMArena French | 1439 | 1505 |
| LMArena German | 1418 | 1498 |
| LMArena Japanese | 1406 | 1512 |
| LMArena Korean | 1384 | 1483 |
| LMArena Russian | 1428 | 1516 |
| LMArena Spanish | 1436 | 1503 |
Instruction Following Gemini 3.7 Flash leads
DeepSeek V4 Flash: 74.9 (#81), Gemini 3.7 Flash: 77.7 (#15)
| Benchmark | DeepSeek V4 Flash | Gemini 3.7 Flash |
|---|---|---|
| LMArena Instruction Following | 1421 | 1483 |
Long Context Gemini 3.7 Flash leads
DeepSeek V4 Flash: 43.8 (#85), Gemini 3.7 Flash: 45.7 (#30)
| Benchmark | DeepSeek V4 Flash | Gemini 3.7 Flash |
|---|---|---|
| LMArena Longer Query | 1434 | 1492 |
Writing & Preference Gemini 3.7 Flash leads
DeepSeek V4 Flash: 63.8 (#61), Gemini 3.7 Flash: 71.2 (#20)
| Benchmark | DeepSeek V4 Flash | Gemini 3.7 Flash |
|---|---|---|
| LMArena Text | 1432 | 1486 |
| LMArena Creative Writing | 1403 | 1490 |
| EQ-Bench Creative Writing | 1559 | 1723 |
| LMArena Multi-Turn | 1449 | 1489 |
Frequently asked questions
Is DeepSeek V4 Flash better than Gemini 3.7 Flash?
Gemini 3.7 Flash is the stronger model overall, scoring 59.8 to 53.6 on the Noometry Index. DeepSeek V4 Flash costs 5.7× less per token, which makes it the better buy when Gemini 3.7 Flash's lead doesn't matter for your workload.
Which is cheaper, DeepSeek V4 Flash or Gemini 3.7 Flash?
DeepSeek V4 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Gemini 3.7 Flash lists at $0.75 and $3.75.
Is DeepSeek V4 Flash or Gemini 3.7 Flash better for coding?
Gemini 3.7 Flash scores higher on coding benchmarks: 56.2 versus 47.9 in the Noometry coding category.
Which has the bigger context window?
Gemini 3.7 Flash does, with 1.05M tokens against 1M.
How many benchmarks do DeepSeek V4 Flash and Gemini 3.7 Flash share?
37 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Gemini 3.7 Flash has 44.