DeepSeek V3.1 Terminus vs Gemini 3.8 Flash
Gemini 3.8 Flash leads DeepSeek V3.1 Terminus on the Artificial Analysis Intelligence Index, 40.9 to 14.8, and DeepSeek V3.1 Terminus costs 3.7x less per output token ($1.0142 vs $3.75 per million). Updated October 21, 2026; 37 benchmarks have a result for both.
vs boards won of 37 shared
DeepSeek V3.1 Terminus or Gemini 3.8 Flash: which to pick
Only Gemini 3.8 Flash has a coding score, 61.6 on the Vibe Coding Index; DeepSeek V3.1 Terminus has none, so the two cannot be ranked on coding.
Pick DeepSeek V3.1 Terminus for output tokens 3.7x cheaper ($1.0142 vs $3.75 per million).
Model ADeepSeek V3.1 TerminusDeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGemini 3.8 FlashGoogle61.6/1006 independent benchmarks$2.74 per solved task
- Shared results
- 37
- DeepSeek V3.1 Terminus only
- 8
- Gemini 3.8 Flash only
- 91
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Gemini 3.8 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 40.9 against 14.8.
Same board, both measured
Agentic work
AA Agentic Index
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 40.2 against 6.8.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Gemini 3.8 Flash has a GPQA Diamond result, 94.4%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.8 Flash has a MMLU Pro result, 90.2%.
Directional only
Web design
Design Arena: websites
Gemini 3.8 Flash
Gemini 3.8 Flash leads, 1300 against 1187.
Same board, both measured
General
Vals Index
No call
Only Gemini 3.8 Flash has a Vals Index result, 56.0%.
Directional only
Long documents
Listed context window
Gemini 3.8 Flash
Gemini 3.8 Flash takes 1.05M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1 Terminus
DeepSeek V3.1 Terminus $0.0008, Gemini 3.8 Flash $0.0026 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.8 Flash has the number, $2.74.
Directional only
At a glance
- Coding index
- DeepSeek V3.1 Terminus not benchmarked, Gemini 3.8 Flash 61.6 from 6 benchmarks.
- Widest category
- Agentic work, 33.4 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Agentic Index: DeepSeek V3.1 Terminus 6.8 against Gemini 3.8 Flash 40.2, 33.4 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 Terminus $1.0142 against Gemini 3.8 Flash $3.75 per million output tokens, 3.7x apart.
- Context window
- DeepSeek V3.1 Terminus takes 164K tokens, Gemini 3.8 Flash 1.05M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | DeepSeek V3.1 Terminus | Bars | Gemini 3.8 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 1 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 7 | ||
| General | 0 | 14 | ||
| All shared boards | 0 | 37 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | DeepSeek V3.1 Terminus | Gemini 3.8 Flash | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 82.2% | Only Gemini 3.8 Flash measured |
| LMArena WebDev | Not measured | 1585 | Only Gemini 3.8 Flash measured |
| AA Coding Index | 43.5 | 76.3 | Gemini 3.8 Flash |
| LiveCodeBench (Vals AI) | Not measured | 89.5% | Only Gemini 3.8 Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 80.0% | Only Gemini 3.8 Flash measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 19.7% | Only Gemini 3.8 Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 78.7% | Only Gemini 3.8 Flash measured |
| Code migration (Vals AI) | Not measured | 36.5% | Only Gemini 3.8 Flash measured |
| ProgramBench (Vals AI) | Not measured | 1.0% | Only Gemini 3.8 Flash measured |
| IOI (Vals AI) | Not measured | 56.9% | Only Gemini 3.8 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 81.3% | Only Gemini 3.8 Flash measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 40.8% | Only Gemini 3.8 Flash measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 18.8% | Only Gemini 3.8 Flash measured |
| SkillsBench (Vals AI) | Not measured | 58.0% | Only Gemini 3.8 Flash measured |
| CyberBench (Vals AI) | Not measured | 43.8% | Only Gemini 3.8 Flash measured |
| LiveCodeBench (Artificial Analysis run) | 79.8% | Not measured | Only DeepSeek V3.1 Terminus measured |
| SciCode | 38.0% | 56.6% | Gemini 3.8 Flash |
| Terminal-Bench Hard (Artificial Analysis run) | 31.8% | Not measured | Only DeepSeek V3.1 Terminus measured |
| FrontierCode | Not measured | 41.2% | Only Gemini 3.8 Flash measured |
| FrontierSWE | Not measured | 19.6% | Only Gemini 3.8 Flash measured |
| WeirdML | Not measured | 84.8% | Only Gemini 3.8 Flash measured |
| ALE-Bench | 745.2 | 1269.7 | Gemini 3.8 Flash |
| LMArena Text: coding | 1425 | 1508 | Gemini 3.8 Flash |
| LMArena Text: software and IT | 1426 | 1507 | Gemini 3.8 Flash |
| LMArena WebDev: React | Not measured | 1577 | Only Gemini 3.8 Flash measured |
| LMArena WebDev: HTML | Not measured | 1616 | Only Gemini 3.8 Flash measured |
| LMArena WebDev: from an image | Not measured | 1593 | Only Gemini 3.8 Flash measured |
| SciCode | Not measured | 12.3% | Only Gemini 3.8 Flash measured |
| Neither model has a result on the other 11 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 Terminus | Gemini 3.8 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.8 | 40.9 | Gemini 3.8 Flash |
| Epoch Capabilities Index | Not measured | 157.4 | Only Gemini 3.8 Flash measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 Terminus | Gemini 3.8 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 6.8 | 40.2 | Gemini 3.8 Flash |
| Design Arena: agents building web apps | Not measured | 1238 | Only Gemini 3.8 Flash measured |
| Design Arena: agents building full-stack apps | Not measured | 1244 | Only Gemini 3.8 Flash measured |
| Design Arena: agents building mobile apps | Not measured | 1236 | Only Gemini 3.8 Flash measured |
| Design Arena: agents building Android apps | Not measured | 1074 | Only Gemini 3.8 Flash measured |
| Design Arena: agents building Godot games | Not measured | 1273 | Only Gemini 3.8 Flash measured |
| Design Arena: PowerPoint slides | Not measured | 1177 | Only Gemini 3.8 Flash measured |
| Design Arena: spreadsheets | Not measured | 1056 | Only Gemini 3.8 Flash measured |
| LiveBench research | Not measured | 79.1% | Only Gemini 3.8 Flash measured |
| LiveBench browser | Not measured | 64.0% | Only Gemini 3.8 Flash measured |
| LiveBench long agentic | Not measured | 30.1% | Only Gemini 3.8 Flash measured |
| SREBench (Vals AI) | Not measured | 11.1% | Only Gemini 3.8 Flash measured |
| Finance Agent (Vals AI) | Not measured | 61.4% | Only Gemini 3.8 Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.1% | Only Gemini 3.8 Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 38.9% | Only Gemini 3.8 Flash measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 12.1% | Only Gemini 3.8 Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 72.2% | Only Gemini 3.8 Flash measured |
| BioMysteryBench (Vals AI) | Not measured | 62.2% | Only Gemini 3.8 Flash measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 8.6% | Only Gemini 3.8 Flash measured |
| Vals Science Index | Not measured | 35.8% | Only Gemini 3.8 Flash measured |
| Time Horizon Index (Vals AI) | Not measured | 18.8% | Only Gemini 3.8 Flash measured |
| CUA-bench (Vals AI) | Not measured | 4.2% | Only Gemini 3.8 Flash measured |
| τ²-Bench Telecom | 37.1% | Not measured | Only DeepSeek V3.1 Terminus measured |
| APEX-Agents | Not measured | 64.3% | Only Gemini 3.8 Flash measured |
| Remote Labor Index | Not measured | 5.8% | Only Gemini 3.8 Flash measured |
| Vending-Bench 2 | Not measured | $5,094 | Only Gemini 3.8 Flash measured |
| Neither model has a result on the other 15 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | DeepSeek V3.1 Terminus | Gemini 3.8 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 94.4% | Only Gemini 3.8 Flash measured |
| LiveBench reasoning | Not measured | 89.3% | Only Gemini 3.8 Flash measured |
| MysteryMechanism (Vals AI) | Not measured | 36.5% | Only Gemini 3.8 Flash measured |
| MMMU Pro (Vals AI) | Not measured | 89.1% | Only Gemini 3.8 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 79.2% | 95.3% | Gemini 3.8 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 16.4% | 47.8% | Gemini 3.8 Flash |
| GPQA Diamond (Epoch AI run) | Not measured | 95.4% | Only Gemini 3.8 Flash measured |
| ARC-AGI | Not measured | 98.5% | Only Gemini 3.8 Flash measured |
| ARC-AGI-2 | Not measured | 89.2% | Only Gemini 3.8 Flash measured |
| Chess puzzles | Not measured | 58.0% | Only Gemini 3.8 Flash measured |
| Mystery game puzzles | Not measured | 47.0% | Only Gemini 3.8 Flash measured |
| LMArena Text: hard prompts | 1426 | 1509 | Gemini 3.8 Flash |
| LMArena Text: expert | Not measured | 1526 | Only Gemini 3.8 Flash measured |
| LMArena Text: hard prompts in English | 1432 | 1504 | Gemini 3.8 Flash |
| LMArena Vision: diagrams | Not measured | 1345 | Only Gemini 3.8 Flash measured |
| LMArena Vision: homework | Not measured | 1351 | Only Gemini 3.8 Flash measured |
| Kagi LLM Benchmark | 57.4% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 Terminus | Gemini 3.8 Flash | Leader |
|---|---|---|---|
| AA Math Index | 89.7 | Not measured | Only DeepSeek V3.1 Terminus measured |
| AIME 2025 (Artificial Analysis run) | 89.7% | Not measured | Only DeepSeek V3.1 Terminus measured |
| OTIS Mock AIME | Not measured | 98.9% | Only Gemini 3.8 Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 68.4% | Only Gemini 3.8 Flash measured |
| FrontierMath, tier 4 | Not measured | 22.0% | Only Gemini 3.8 Flash measured |
| ProofBench | Not measured | 48.0% | Only Gemini 3.8 Flash measured |
| LMArena Text: math | 1402 | 1532 | Gemini 3.8 Flash |
| LMArena Text: mathematical work | Not measured | 1519 | Only Gemini 3.8 Flash measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | DeepSeek V3.1 Terminus | Gemini 3.8 Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 90.2% | Only Gemini 3.8 Flash measured |
| LegalBench (Vals AI) | Not measured | 87.0% | Only Gemini 3.8 Flash measured |
| TaxEval (Vals AI) | Not measured | 74.5% | Only Gemini 3.8 Flash measured |
| MortgageTax (Vals AI) | Not measured | 65.3% | Only Gemini 3.8 Flash measured |
| MedCode (Vals AI) | Not measured | 48.1% | Only Gemini 3.8 Flash measured |
| MMLU Pro (Artificial Analysis run) | 85.1% | Not measured | Only DeepSeek V3.1 Terminus measured |
| SimpleQA Verified | Not measured | 69.7% | Only Gemini 3.8 Flash measured |
| LMArena Text: science | 1451 | 1523 | Gemini 3.8 Flash |
| LMArena Text: medicine and healthcare | 1468 | 1508 | Gemini 3.8 Flash |
| LMArena Text: legal and government | 1457 | 1497 | Gemini 3.8 Flash |
| LMArena Text: business and finance | 1414 | 1479 | Gemini 3.8 Flash |
| FACTS Benchmark Suite | Not measured | 69.4% | Only Gemini 3.8 Flash measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V3.1 Terminus | Gemini 3.8 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1187 | 1300 | Gemini 3.8 Flash |
| Design Arena: UI components | 1182 | 1319 | Gemini 3.8 Flash |
| Design Arena: game dev | 1131 | 1305 | Gemini 3.8 Flash |
| Design Arena: data viz | 1167 | 1269 | Gemini 3.8 Flash |
| Design Arena: 3D | 1141 | 1295 | Gemini 3.8 Flash |
| Design Arena: all code categories | 1175 | 1304 | Gemini 3.8 Flash |
| Design Arena: SVG | 1065 | 1295 | Gemini 3.8 Flash |
| Design Arena: ASCII art | Not measured | 1265 | Only Gemini 3.8 Flash measured |
| LiveBench design | Not measured | 72.7% | Only Gemini 3.8 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index014
| Benchmark | DeepSeek V3.1 Terminus | Gemini 3.8 Flash | Leader |
|---|---|---|---|
| Vals Index | Not measured | 56.0% | Only Gemini 3.8 Flash measured |
| LiveBench data analysis | Not measured | 54.0% | Only Gemini 3.8 Flash measured |
| Public Benefits Bench (Vals AI) | Not measured | 65.3% | Only Gemini 3.8 Flash measured |
| SAGE (Vals AI) | Not measured | 35.1% | Only Gemini 3.8 Flash measured |
| MedScribe (Vals AI) | Not measured | 84.5% | Only Gemini 3.8 Flash measured |
| IFBench | 57.0% | Not measured | Only DeepSeek V3.1 Terminus measured |
| Long context reasoning (AA-LCR) | 69.3% | 84.0% | Gemini 3.8 Flash |
| DTBench | 81.3% | 95.7% | Gemini 3.8 Flash |
| LMCA | 28.6% | 52.9% | Gemini 3.8 Flash |
| Surface Evolver Bench | Not measured | 76.9% | Only Gemini 3.8 Flash measured |
| Furniture assembly | Not measured | 31.7% | Only Gemini 3.8 Flash measured |
| LMArena Text | 1419 | 1499 | Gemini 3.8 Flash |
| LMArena Text: instruction following | 1404 | 1492 | Gemini 3.8 Flash |
| LMArena Text: creative writing | 1403 | 1488 | Gemini 3.8 Flash |
| LMArena Vision | Not measured | 1315 | Only Gemini 3.8 Flash measured |
| LMArena Text: English | 1429 | 1498 | Gemini 3.8 Flash |
| LMArena Text: non-English | 1408 | 1491 | Gemini 3.8 Flash |
| LMArena Text: Chinese | Not measured | 1553 | Only Gemini 3.8 Flash measured |
| LMArena Text: German | Not measured | 1501 | Only Gemini 3.8 Flash measured |
| LMArena Text: Japanese | Not measured | 1507 | Only Gemini 3.8 Flash measured |
| LMArena Text: Korean | Not measured | 1464 | Only Gemini 3.8 Flash measured |
| LMArena Text: French | Not measured | 1496 | Only Gemini 3.8 Flash measured |
| LMArena Text: Spanish | Not measured | 1487 | Only Gemini 3.8 Flash measured |
| LMArena Text: Russian | 1435 | 1514 | Gemini 3.8 Flash |
| LMArena Text: Polish | 1427 | 1497 | Gemini 3.8 Flash |
| LMArena Text: multi-turn | 1411 | 1503 | Gemini 3.8 Flash |
| LMArena Text: longer queries | 1422 | 1507 | Gemini 3.8 Flash |
| LMArena Text: writing and language | 1409 | 1494 | Gemini 3.8 Flash |
| LMArena Text: entertainment and media | 1391 | 1480 | Gemini 3.8 Flash |
| LMArena Vision: English | Not measured | 1318 | Only Gemini 3.8 Flash measured |
| LMArena Vision: Chinese | Not measured | 1416 | Only Gemini 3.8 Flash measured |
| LMArena Vision: reading text | Not measured | 1333 | Only Gemini 3.8 Flash measured |
| LMArena Vision: humor | Not measured | 1321 | Only Gemini 3.8 Flash measured |
| LMArena Vision: creative writing | Not measured | 1299 | Only Gemini 3.8 Flash measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 Terminus | Gemini 3.8 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
DeepSeek V3.1 Terminus$0.0008Fits in one request
Gemini 3.8 Flash$0.0026Fits in one request
DeepSeek V3.1 Terminus costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.1 Terminus$0.018Fits in one request
Gemini 3.8 Flash$0.049Fits in one request
DeepSeek V3.1 Terminus costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.1 Terminus$0.071Exceeds the context window
Gemini 3.8 Flash$0.188Fits in one request
DeepSeek V3.1 Terminus costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | DeepSeek V3.1 Terminus | Google Gemini 3.8 Flash |
|---|---|---|
| Maker | DeepSeek | |
| Weights | Open weights | No public weights listed |
| Released | September 22, 2025 | September 2, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.3063 | $0.75 |
| Output $/Mtok | $1.0142 | $3.75 |
| Coding index | Not benchmarked | 61.6 |
| Independent measurements behind it | 0 | 6 |
| Cost per solved task | Not computable | $2.74 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.1 Terminus better than Gemini 3.8 Flash for coding?
Only Gemini 3.8 Flash has a coding score, 61.6 on the Vibe Coding Index; DeepSeek V3.1 Terminus has none, so the two cannot be ranked on coding. Pick DeepSeek V3.1 Terminus for output tokens 3.7x cheaper ($1.0142 vs $3.75 per million).
Which is cheaper, DeepSeek V3.1 Terminus or Gemini 3.8 Flash?
DeepSeek V3.1 Terminus costs $0.3063 per million input tokens and $1.0142 per million output tokens; Gemini 3.8 Flash costs $0.75 and $3.75. Cost per solved task is known for Gemini 3.8 Flash only.
Which has the bigger context window, DeepSeek V3.1 Terminus or Gemini 3.8 Flash?
Gemini 3.8 Flash, with 1.05M tokens against 164K.
How many benchmarks is the DeepSeek V3.1 Terminus vs Gemini 3.8 Flash comparison based on?
37 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.1 Terminus's coding index rests on 0 independent benchmarks and Gemini 3.8 Flash's on 6. Where only one model has a result, the page says so instead of naming a winner.