Gemini 2.5 Pro Preview 06-05 vs Mistral Nemo
Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
- Coding
- No data
- Overall
- No data
- Output $/M
- $10.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Gemini 2.5 Pro Preview 06-05 has the edge where the context window is larger, 1.05M against 131K tokens.
- Shared results
- 0
- Gemini 2.5 Pro Preview 06-05 only
- 14
- Mistral Nemo only
- 3
- Like-for-like categories
- 0 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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
Neither has a coding score yet.
One side not measured
Long documents
Listed context window
Gemini 2.5 Pro Preview 06-05
Gemini 2.5 Pro Preview 06-05 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Nemo
Gemini 2.5 Pro Preview 06-05 $0.0063, Mistral Nemo $0.0002 per turn.
List prices
At a glance
- Coding index
- Gemini 2.5 Pro Preview 06-05 not benchmarked, Mistral Nemo not benchmarked.
- Widest category
- No category has a result for both models.
- Widest single gap
- No benchmark has a result for both models.
- Output price
- Gemini 2.5 Pro Preview 06-05 $10.00 against Mistral Nemo $0.15 per million output tokens, 66.7x apart.
- Context window
- Gemini 2.5 Pro Preview 06-05 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.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Mistral Nemo | Leader |
|---|---|---|---|
| Aider polyglot | 83.1% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| LiveCodeBench (Vals AI) | 79.2% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| LiveCodeBench (Artificial Analysis run) | 77.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Mistral Nemo | Leader |
|---|---|---|---|
| Epoch Capabilities Index | Not measured | 118.7 | Only Mistral Nemo measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Mistral Nemo | Leader |
|---|---|---|---|
| METR time horizons | 55.4% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Remote Labor Index | 0.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| DeepResearch Bench | 42.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Mistral Nemo | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 83.6% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Humanity's Last Exam (Artificial Analysis run) | 19.9% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| GPQA Diamond (Epoch AI run) | 84.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| SimpleBench | 62.4% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| VPCT | 46.4% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 16 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Mistral Nemo | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Mistral Nemo | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 85.8% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| MMLU | Not measured | 65.3% | Only Mistral Nemo measured |
| Neither model has a result on the other 15 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Mistral Nemo | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | Mistral Nemo | Leader |
|---|---|---|---|
| DTBench | Not measured | 48.6% | Only Mistral Nemo measured |
| Fiction.LiveBench | 91.7% | Not measured | Only Gemini 2.5 Pro Preview 06-05 measured |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro Preview 06-05 | 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 2.5 Pro Preview 06-05 | Mistral Nemo |
|---|---|---|
| Maker | Mistral AI | |
| Weights | No public weights listed | Open weights |
| Released | June 5, 2025 | July 19, 2024 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $1.25 | $0.15 |
| Output $/Mtok | $10.00 | $0.15 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro Preview 06-05 better than Mistral Nemo for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Gemini 2.5 Pro Preview 06-05 has the edge where the context window is larger, 1.05M against 131K tokens.
Which is cheaper, Gemini 2.5 Pro Preview 06-05 or Mistral Nemo?
Gemini 2.5 Pro Preview 06-05 costs $1.25 per million input tokens and $10.00 per million output tokens; Mistral Nemo costs $0.15 and $0.15. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemini 2.5 Pro Preview 06-05 or Mistral Nemo?
Gemini 2.5 Pro Preview 06-05, with 1.05M tokens against 131K.
How many benchmarks is the Gemini 2.5 Pro Preview 06-05 vs Mistral Nemo comparison based on?
0 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Pro Preview 06-05's coding index rests on 0 independent benchmarks and Mistral Nemo's on 0. Where only one model has a result, the page says so instead of naming a winner.