Codestral 2508 vs Nemotron 3.5 Super VL
Nemotron 3.5 Super VL costs 1.8x less per output token than Codestral 2508 ($0.50 vs $0.90 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
Codestral 2508 or Nemotron 3.5 Super VL: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Codestral 2508 for work measured by Design Arena: websites or Design Arena: UI components, where it leads.
- Shared results
- 5
- Codestral 2508 only
- 3
- Nemotron 3.5 Super VL only
- 11
- Like-for-like categories
- 1 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Nemotron 3.5 Super VL has a AA Intelligence Index result, 26.5.
Directional only
Web design
Design Arena: websites
Nemotron 3.5 Super VL
Nemotron 3.5 Super VL leads, 1172 against 1012.
Same board, both measured
Long documents
Listed context window
Nemotron 3.5 Super VL
Nemotron 3.5 Super VL takes 1.05M tokens against 256K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3.5 Super VL
Codestral 2508 $0.0008, Nemotron 3.5 Super VL $0.0004 per turn.
List prices
At a glance
- Coding index
- Codestral 2508 not benchmarked, Nemotron 3.5 Super VL not benchmarked.
- Widest category
- Web design, 17.4 points apart on average over 5 shared benchmarks.
- Widest single gap
- Design Arena: websites: Codestral 2508 1012 against Nemotron 3.5 Super VL 1172, 20.0 points apart on a 0 to 100 scale.
- Output price
- Codestral 2508 $0.90 against Nemotron 3.5 Super VL $0.50 per million output tokens, 1.8x apart.
- Context window
- Codestral 2508 takes 256K tokens, Nemotron 3.5 Super VL 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 | Codestral 2508 | Bars | Nemotron 3.5 Super VL | Ties |
|---|---|---|---|---|
| Web design | 0 | 5 | ||
| All shared boards | 0 | 5 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards, none shared
| Benchmark | Codestral 2508 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 65.5% | Only Nemotron 3.5 Super VL measured |
| SciCode | Not measured | 47.8% | Only Nemotron 3.5 Super VL measured |
| ALE-Bench | 137.8 | Not measured | Only Codestral 2508 measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Codestral 2508 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 26.5 | Only Nemotron 3.5 Super VL 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 | Codestral 2508 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 70.9% | Only Nemotron 3.5 Super VL measured |
| LiveBench browser | Not measured | 4.0% | Only Nemotron 3.5 Super VL measured |
| LiveBench long agentic | Not measured | 15.8% | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Codestral 2508 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 78.8% | Only Nemotron 3.5 Super VL measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 30.7% | Only Nemotron 3.5 Super VL measured |
| Kagi LLM Benchmark | 32.5% | Not measured | Only Codestral 2508 measured |
| Neither model has a result on the other 19 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Codestral 2508 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Codestral 2508 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Codestral 2508 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| Design Arena: websites | 1012 | 1172 | Nemotron 3.5 Super VL |
| Design Arena: UI components | 1014 | 1153 | Nemotron 3.5 Super VL |
| Design Arena: game dev | 967 | 1110 | Nemotron 3.5 Super VL |
| Design Arena: data viz | 1017 | Not measured | Only Codestral 2508 measured |
| Design Arena: 3D | 1019 | 1127 | Nemotron 3.5 Super VL |
| Design Arena: all code categories | 1007 | 1155 | Nemotron 3.5 Super VL |
| LiveBench design | Not measured | 60.7% | Only Nemotron 3.5 Super VL measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Codestral 2508 | Nemotron 3.5 Super VL | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 64.6% | Only Nemotron 3.5 Super VL measured |
| Long context reasoning (AA-LCR) | Not measured | 69.0% | Only Nemotron 3.5 Super VL 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 | Codestral 2508 | Nemotron 3.5 Super VL | 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
Nemotron 3.5 Super VL costs less
Repository review
50K input + 3K output tokens
Nemotron 3.5 Super VL costs less
Agent loop
200K input + 10K output tokens
Nemotron 3.5 Super VL 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 | Mistral Codestral 2508 | NVIDIA Nemotron 3.5 Super VL |
|---|---|---|
| Maker | Mistral AI | NVIDIA |
| Weights | No public weights listed | Open weights |
| Released | August 1, 2025 | October 15, 2026 |
| Context window | 256K | 1.05M |
| Input $/Mtok | $0.30 | $0.15 |
| Output $/Mtok | $0.90 | $0.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Codestral 2508 better than Nemotron 3.5 Super VL for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Codestral 2508 for work measured by Design Arena: websites or Design Arena: UI components, where it leads.
Which is cheaper, Codestral 2508 or Nemotron 3.5 Super VL?
Codestral 2508 costs $0.30 per million input tokens and $0.90 per million output tokens; Nemotron 3.5 Super VL costs $0.15 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, Codestral 2508 or Nemotron 3.5 Super VL?
Nemotron 3.5 Super VL, with 1.05M tokens against 256K.
How many benchmarks is the Codestral 2508 vs Nemotron 3.5 Super VL comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. Codestral 2508's coding index rests on 0 independent benchmarks and Nemotron 3.5 Super VL's on 1. Where only one model has a result, the page says so instead of naming a winner.