Ling 3.0 Flash vs Mistral Nemo
Ling 3.0 Flash costs 1.2x less per output token than Mistral Nemo ($0.1215 vs $0.15 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- 29.6
- Overall
- No data
- Output $/M
- $0.1215
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
Ling 3.0 Flash or Mistral Nemo: which to pick
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; Mistral Nemo has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Ling 3.0 Flash has results on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI); 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
Only Ling 3.0 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Ling 3.0 Flash has a AA Intelligence Index result, 20.1.
Directional only
Agentic work
AA Agentic Index
No call
Only Ling 3.0 Flash has a AA Agentic Index result, 19.3.
Directional only
Reasoning
GPQA Diamond
No call
Only Ling 3.0 Flash has a GPQA Diamond result, 84.8%.
Directional only
Knowledge
MMLU Pro
No call
Only Ling 3.0 Flash has a MMLU Pro result, 82.0%.
Directional only
Long documents
Listed context window
Ling 3.0 Flash
Ling 3.0 Flash takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
Ling 3.0 Flash $0.0001, Mistral Nemo $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Ling 3.0 Flash has the number, $0.05.
Directional only
At a glance
- Coding index
- Ling 3.0 Flash 29.6 from 2 benchmarks, 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
- Ling 3.0 Flash $0.1215 against Mistral Nemo $0.15 per million output tokens, 1.2x apart.
- Context window
- Ling 3.0 Flash takes 262K tokens, Mistral Nemo 131K.
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 Index8 boards measured
| Benchmark | Ling 3.0 Flash | Mistral Nemo | Leader |
|---|---|---|---|
| AA Coding Index | 50.6 | Not measured | Only Ling 3.0 Flash measured |
| LiveCodeBench (Vals AI) | 84.0% | Not measured | Only Ling 3.0 Flash measured |
| SWE-bench Verified (Vals AI) | 65.2% | Not measured | Only Ling 3.0 Flash measured |
| Vibe Code Bench (Vals AI) | 2.9% | Not measured | Only Ling 3.0 Flash measured |
| Code migration (Vals AI) | 0.0% | Not measured | Only Ling 3.0 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | Not measured | Only Ling 3.0 Flash measured |
| SkillsBench (Vals AI) | 27.9% | Not measured | Only Ling 3.0 Flash measured |
| SciCode | 42.0% | Not measured | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Ling 3.0 Flash | Mistral Nemo | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.1 | Not measured | Only Ling 3.0 Flash measured |
| Epoch Capabilities Index | Not measured | 118.7 | Only Mistral Nemo measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Ling 3.0 Flash | Mistral Nemo | Leader |
|---|---|---|---|
| AA Agentic Index | 19.3 | Not measured | Only Ling 3.0 Flash measured |
| Finance Agent (Vals AI) | 30.3% | Not measured | Only Ling 3.0 Flash measured |
| Legal Research Bench (Vals AI) | 0.0% | Not measured | Only Ling 3.0 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 25.0% | Not measured | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Ling 3.0 Flash | Mistral Nemo | Leader |
|---|---|---|---|
| GPQA Diamond | 84.8% | Not measured | Only Ling 3.0 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 85.5% | Not measured | Only Ling 3.0 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 23.7% | Not measured | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 19 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Ling 3.0 Flash | Mistral Nemo | Leader |
|---|---|---|---|
| MMLU Pro | 82.0% | Not measured | Only Ling 3.0 Flash measured |
| LegalBench (Vals AI) | 79.7% | Not measured | Only Ling 3.0 Flash measured |
| CorpFin (Vals AI) | 61.9% | Not measured | Only Ling 3.0 Flash measured |
| TaxEval (Vals AI) | 70.7% | Not measured | Only Ling 3.0 Flash measured |
| MedCode (Vals AI) | 32.3% | Not measured | Only Ling 3.0 Flash measured |
| MMLU | Not measured | 65.3% | Only Mistral Nemo measured |
| Neither model has a result on the other 12 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Ling 3.0 Flash | Mistral Nemo | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 50.7% | Not measured | Only Ling 3.0 Flash measured |
| MedScribe (Vals AI) | 80.9% | Not measured | Only Ling 3.0 Flash measured |
| Long context reasoning (AA-LCR) | 73.0% | Not measured | Only Ling 3.0 Flash measured |
| DTBench | Not measured | 48.6% | Only Mistral Nemo measured |
| Neither model has a result on the other 42 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
Ling 3.0 Flash costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 Flash 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 | inclusionAI Ling 3.0 Flash | Mistral Nemo |
|---|---|---|
| Maker | inclusionAI | Mistral AI |
| Weights | Open weights | Open weights |
| Released | July 23, 2026 | July 19, 2024 |
| Context window | 262K | 131K |
| Input $/Mtok | $0.0405 | $0.15 |
| Output $/Mtok | $0.1215 | $0.15 |
| Coding index | 29.6 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | $0.05 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ling 3.0 Flash better than Mistral Nemo for coding?
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; Mistral Nemo has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Ling 3.0 Flash or Mistral Nemo?
Ling 3.0 Flash costs $0.0405 per million input tokens and $0.1215 per million output tokens; Mistral Nemo costs $0.15 and $0.15. Cost per solved task is known for Ling 3.0 Flash only.
Which has the bigger context window, Ling 3.0 Flash or Mistral Nemo?
Ling 3.0 Flash, with 262K tokens against 131K.
Has any benchmark tested both Ling 3.0 Flash and Mistral Nemo?
No benchmark has tested both yet. Ling 3.0 Flash has results on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI); Mistral Nemo on Epoch Capabilities Index, MMLU and DTBench. Compare them on price and context instead. Data as of October 21, 2026.