Gemini 3.5 Flash Lite vs Mistral Nemo
Mistral Nemo costs 16.7x less per output token than Gemini 3.5 Flash Lite ($0.15 vs $2.50 per million). Updated October 21, 2026; 2 benchmarks have a result for both.
Gemini 3.5 Flash Lite or Mistral Nemo: which to pick
Only Gemini 3.5 Flash Lite has a coding score, 49.0 on the Vibe Coding Index; Mistral Nemo has none, so the two cannot be ranked on coding.
Pick Mistral Nemo for output tokens 16.7x cheaper ($0.15 vs $2.50 per million).
- Shared results
- 2
- Gemini 3.5 Flash Lite only
- 83
- Mistral Nemo only
- 1
- Like-for-like categories
- 2 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 3.5 Flash Lite has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Gemini 3.5 Flash Lite has a AA Intelligence Index result, 22.2.
Directional only
Agentic work
AA Agentic Index
No call
Only Gemini 3.5 Flash Lite has a AA Agentic Index result, 14.3.
Directional only
Reasoning
GPQA Diamond
No call
Only Gemini 3.5 Flash Lite has a GPQA Diamond result, 83.8%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.5 Flash Lite has a MMLU Pro result, 85.8%.
Directional only
Long documents
Listed context window
Gemini 3.5 Flash Lite
Gemini 3.5 Flash Lite takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Nemo
Gemini 3.5 Flash Lite $0.0015, Mistral Nemo $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.5 Flash Lite has the number, $0.41.
Directional only
At a glance
- Coding index
- Gemini 3.5 Flash Lite 49.0 from 3 benchmarks, Mistral Nemo not benchmarked.
- Widest category
- General, 34.9 points apart on average over 1 shared benchmark.
- Widest single gap
- DTBench: Gemini 3.5 Flash Lite 83.5% against Mistral Nemo 48.6%, 34.9 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.5 Flash Lite $2.50 against Mistral Nemo $0.15 per million output tokens, 16.7x apart.
- Context window
- Gemini 3.5 Flash Lite takes 1.05M tokens, Mistral Nemo 131K.
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 | Gemini 3.5 Flash Lite | Bars | Mistral Nemo | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 2 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index17 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | Mistral Nemo | Leader |
|---|---|---|---|
| LMArena WebDev | 1435 | Not measured | Only Gemini 3.5 Flash Lite measured |
| AA Coding Index | 49.3 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LiveCodeBench (Vals AI) | 79.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| SWE-bench Verified (Vals AI) | 75.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Vibe Code Bench (Vals AI) | 37.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Code migration (Vals AI) | 6.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| CyberBench (Vals AI) | 59.1% | Not measured | Only Gemini 3.5 Flash Lite measured |
| SciCode | 41.3% | Not measured | Only Gemini 3.5 Flash Lite measured |
| WeirdML | 39.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| ALE-Bench | 765.3 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: coding | 1453 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: software and IT | 1451 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena WebDev: React | 1408 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena WebDev: from an image | 1448 | Not measured | Only Gemini 3.5 Flash Lite measured |
| SciCode | 6.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 3.5 Flash Lite | Mistral Nemo | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.2 | Not measured | Only Gemini 3.5 Flash Lite measured |
| Epoch Capabilities Index | 144.9 | 118.7 | Gemini 3.5 Flash Lite |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | Mistral Nemo | Leader |
|---|---|---|---|
| AA Agentic Index | 14.3 | Not measured | Only Gemini 3.5 Flash Lite measured |
| Finance Agent (Vals AI) | 47.4% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Tax Agent Bench (Vals AI) | 7.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Legal Research Bench (Vals AI) | 13.9% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Excel Modeling Benchmark (Vals AI) | 43.2% | Not measured | Only Gemini 3.5 Flash Lite measured |
| APEX-Agents | 29.3% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | Mistral Nemo | Leader |
|---|---|---|---|
| GPQA Diamond | 83.8% | Not measured | Only Gemini 3.5 Flash Lite measured |
| MMMU Pro (Vals AI) | 83.6% | Not measured | Only Gemini 3.5 Flash Lite measured |
| GPQA Diamond (Artificial Analysis run) | 83.8% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Humanity's Last Exam (Artificial Analysis run) | 18.8% | Not measured | Only Gemini 3.5 Flash Lite measured |
| GPQA Diamond (Epoch AI run) | 83.3% | Not measured | Only Gemini 3.5 Flash Lite measured |
| ARC-AGI | 53.5% | Not measured | Only Gemini 3.5 Flash Lite measured |
| ARC-AGI-2 | 10.3% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Chess puzzles | 21.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Mystery game puzzles | 19.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: hard prompts | 1441 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: expert | 1434 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: hard prompts in English | 1440 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: diagrams | 1284 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: homework | 1291 | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 8 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | Mistral Nemo | Leader |
|---|---|---|---|
| OTIS Mock AIME | 71.1% | Not measured | Only Gemini 3.5 Flash Lite measured |
| FrontierMath, tiers 1 to 3 | 26.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| FrontierMath, tier 4 | 0.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| ProofBench | 13.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: math | 1434 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: mathematical work | 1433 | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | Mistral Nemo | Leader |
|---|---|---|---|
| MMLU Pro | 85.8% | Not measured | Only Gemini 3.5 Flash Lite measured |
| LegalBench (Vals AI) | 84.1% | Not measured | Only Gemini 3.5 Flash Lite measured |
| CorpFin (Vals AI) | 60.7% | Not measured | Only Gemini 3.5 Flash Lite measured |
| TaxEval (Vals AI) | 72.6% | Not measured | Only Gemini 3.5 Flash Lite measured |
| MortgageTax (Vals AI) | 68.7% | Not measured | Only Gemini 3.5 Flash Lite measured |
| MedCode (Vals AI) | 43.5% | Not measured | Only Gemini 3.5 Flash Lite measured |
| MMLU | Not measured | 65.3% | Only Mistral Nemo measured |
| LMArena Text: science | 1451 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: medicine and healthcare | 1438 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: legal and government | 1431 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: business and finance | 1423 | Not measured | Only Gemini 3.5 Flash Lite measured |
| FACTS Benchmark Suite | 53.5% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 6 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | Mistral Nemo | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemini 3.5 Flash Lite | Mistral Nemo | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 51.8% | Not measured | Only Gemini 3.5 Flash Lite measured |
| SAGE (Vals AI) | 47.3% | Not measured | Only Gemini 3.5 Flash Lite measured |
| MedScribe (Vals AI) | 70.9% | Not measured | Only Gemini 3.5 Flash Lite measured |
| Long context reasoning (AA-LCR) | 76.0% | Not measured | Only Gemini 3.5 Flash Lite measured |
| DTBench | 83.5% | 48.6% | Gemini 3.5 Flash Lite |
| LMCA | 37.6% | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text | 1435 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: instruction following | 1419 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: creative writing | 1421 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision | 1269 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: English | 1438 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: non-English | 1427 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Chinese | 1468 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: German | 1454 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Japanese | 1426 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Korean | 1407 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: French | 1451 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Spanish | 1441 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Russian | 1443 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: Polish | 1437 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: multi-turn | 1445 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: longer queries | 1435 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: writing and language | 1428 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Text: entertainment and media | 1414 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: English | 1269 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: Chinese | 1311 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: reading text | 1280 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: humor | 1287 | Not measured | Only Gemini 3.5 Flash Lite measured |
| LMArena Vision: creative writing | 1260 | Not measured | Only Gemini 3.5 Flash Lite measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.5 Flash Lite | Mistral Nemo | 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
Mistral Nemo costs less
Repository review
50K input + 3K output tokens
Mistral Nemo costs less
Agent loop
200K input + 10K output tokens
Mistral Nemo 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 | Google Gemini 3.5 Flash Lite | Mistral Nemo |
|---|---|---|
| Maker | Mistral AI | |
| Weights | No public weights listed | Open weights |
| Released | July 21, 2026 | July 19, 2024 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $0.30 | $0.15 |
| Output $/Mtok | $2.50 | $0.15 |
| Coding index | 49.0 | Not benchmarked |
| Independent measurements behind it | 3 | 0 |
| Cost per solved task | $0.41 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.5 Flash Lite better than Mistral Nemo for coding?
Only Gemini 3.5 Flash Lite has a coding score, 49.0 on the Vibe Coding Index; Mistral Nemo has none, so the two cannot be ranked on coding. Pick Mistral Nemo for output tokens 16.7x cheaper ($0.15 vs $2.50 per million).
Which is cheaper, Gemini 3.5 Flash Lite or Mistral Nemo?
Gemini 3.5 Flash Lite costs $0.30 per million input tokens and $2.50 per million output tokens; Mistral Nemo costs $0.15 and $0.15. Cost per solved task is known for Gemini 3.5 Flash Lite only.
Which has the bigger context window, Gemini 3.5 Flash Lite or Mistral Nemo?
Gemini 3.5 Flash Lite, with 1.05M tokens against 131K.
How many benchmarks is the Gemini 3.5 Flash Lite vs Mistral Nemo comparison based on?
2 benchmarks have a result for both models as of October 21, 2026. Gemini 3.5 Flash Lite's coding index rests on 3 independent benchmarks and Mistral Nemo's on 0. Where only one model has a result, the page says so instead of naming a winner.