Granite 4.2 8B vs Mistral Nemo
Mistral Nemo costs 1.3x less per output token than Granite 4.2 8B ($0.15 vs $0.20 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.20
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
Granite 4.2 8B or Mistral Nemo: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Granite 4.2 8B has results on AA Coding Index, SciCode and LMArena Text: coding; Mistral Nemo on Epoch Capabilities Index, MMLU and DTBench. Compare them on price and context instead.
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
Intelligence
AA Intelligence Index
No call
Only Granite 4.2 8B has a AA Intelligence Index result, 11.1.
Directional only
Agentic work
AA Agentic Index
No call
Only Granite 4.2 8B has a AA Agentic Index result, 1.3.
Directional only
Long documents
Listed context window
No call
Both take 131K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Granite 4.2 8B
Granite 4.2 8B $0.0002, Mistral Nemo $0.0002 per turn.
List prices
At a glance
- Coding index
- Granite 4.2 8B not benchmarked, Mistral Nemo not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Granite 4.2 8B $0.20 against Mistral Nemo $0.15 per million output tokens, 1.3x apart.
- Context window
- Both take 131K tokens.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
| Benchmark | Granite 4.2 8B | Mistral Nemo | Leader |
|---|---|---|---|
| AA Coding Index | 22.4 | Not measured | Only Granite 4.2 8B measured |
| SciCode | 31.5% | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: coding | 1378 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: software and IT | 1367 | Not measured | Only Granite 4.2 8B measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Granite 4.2 8B | Mistral Nemo | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.1 | Not measured | Only Granite 4.2 8B measured |
| Epoch Capabilities Index | Not measured | 118.7 | Only Mistral Nemo measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Granite 4.2 8B | Mistral Nemo | Leader |
|---|---|---|---|
| AA Agentic Index | 1.3 | Not measured | Only Granite 4.2 8B measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Granite 4.2 8B | Mistral Nemo | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 63.1% | Not measured | Only Granite 4.2 8B measured |
| Humanity's Last Exam (Artificial Analysis run) | 9.7% | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: hard prompts | 1327 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: expert | 1386 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: hard prompts in English | 1345 | Not measured | Only Granite 4.2 8B measured |
| Neither model has a result on the other 17 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Granite 4.2 8B | Mistral Nemo | Leader |
|---|---|---|---|
| MMLU | Not measured | 65.3% | Only Mistral Nemo measured |
| LMArena Text: science | 1336 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: medicine and healthcare | 1336 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: legal and government | 1327 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: business and finance | 1322 | Not measured | Only Granite 4.2 8B measured |
| Neither model has a result on the other 13 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index13 boards measured
| Benchmark | Granite 4.2 8B | Mistral Nemo | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | 45.0% | Not measured | Only Granite 4.2 8B measured |
| DTBench | Not measured | 48.6% | Only Mistral Nemo measured |
| LMArena Text | 1319 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: instruction following | 1300 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: creative writing | 1236 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: English | 1337 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: non-English | 1301 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: Chinese | 1367 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: Russian | 1282 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: multi-turn | 1301 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: longer queries | 1325 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: writing and language | 1269 | Not measured | Only Granite 4.2 8B measured |
| LMArena Text: entertainment and media | 1271 | Not measured | Only Granite 4.2 8B measured |
| Neither model has a result on the other 33 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
Granite 4.2 8B costs less
Repository review
50K input + 3K output tokens
Granite 4.2 8B costs less
Agent loop
200K input + 10K output tokens
Granite 4.2 8B 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 | IBM Granite 4.2 8B | Mistral Nemo |
|---|---|---|
| Maker | IBM Granite | Mistral AI |
| Weights | Open weights | Open weights |
| Released | August 31, 2026 | July 19, 2024 |
| Context window | 131K | 131K |
| Input $/Mtok | $0.08 | $0.15 |
| Output $/Mtok | $0.20 | $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 Granite 4.2 8B better than Mistral Nemo for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Granite 4.2 8B or Mistral Nemo?
Granite 4.2 8B costs $0.08 per million input tokens and $0.20 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, Granite 4.2 8B or Mistral Nemo?
Neither: both take 131K tokens.
Has any benchmark tested both Granite 4.2 8B and Mistral Nemo?
No benchmark has tested both yet. Granite 4.2 8B has results on AA Coding Index, SciCode and LMArena Text: coding; Mistral Nemo on Epoch Capabilities Index, MMLU and DTBench. Compare them on price and context instead. Data as of October 22, 2026.