Qwen2.5 Coder 32B Instruct vs Voxtral Small 24B 2507
Voxtral Small 24B 2507 costs 3.3x less per output token than Qwen2.5 Coder 32B Instruct ($0.30 vs $1.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.30
Qwen2.5 Coder 32B Instruct or Voxtral Small 24B 2507: 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. Qwen2.5 Coder 32B Instruct has results on Aider polyglot, SWE-bench Verified and LiveCodeBench (Artificial Analysis run); Voxtral Small 24B 2507 has none yet. 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 Qwen2.5 Coder 32B Instruct has a AA Intelligence Index result, 6.7.
Directional only
Long documents
Listed context window
No call
Both take 33K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Voxtral Small 24B 2507
Qwen2.5 Coder 32B Instruct $0.0012, Voxtral Small 24B 2507 $0.0003 per turn.
List prices
At a glance
- Coding index
- Qwen2.5 Coder 32B Instruct not benchmarked, Voxtral Small 24B 2507 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
- Qwen2.5 Coder 32B Instruct $1.00 against Voxtral Small 24B 2507 $0.30 per million output tokens, 3.3x apart.
- Context window
- Both take 33K 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 Index5 boards measured
| Benchmark | Qwen2.5 Coder 32B Instruct | Voxtral Small 24B 2507 | Leader |
|---|---|---|---|
| Aider polyglot | 16.4% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| SWE-bench Verified | 47.0% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LiveCodeBench (Artificial Analysis run) | 29.5% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: coding | 1276 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: software and IT | 1261 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen2.5 Coder 32B Instruct | Voxtral Small 24B 2507 | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| Epoch Capabilities Index | 119.5 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Qwen2.5 Coder 32B Instruct | Voxtral Small 24B 2507 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 41.7% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | 3.5% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: hard prompts | 1251 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: expert | 1221 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: hard prompts in English | 1269 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Qwen2.5 Coder 32B Instruct | Voxtral Small 24B 2507 | Leader |
|---|---|---|---|
| GSM8K | 93.0% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: math | 1251 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: mathematical work | 1243 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Qwen2.5 Coder 32B Instruct | Voxtral Small 24B 2507 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 63.5% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| MMLU | 79.1% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| AI2 Reasoning Challenge | 70.5% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: science | 1221 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: medicine and healthcare | 1187 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: legal and government | 1257 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: business and finance | 1224 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| Neither model has a result on the other 11 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index13 boards measured
| Benchmark | Qwen2.5 Coder 32B Instruct | Voxtral Small 24B 2507 | Leader |
|---|---|---|---|
| HellaSwag | 83.0% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| WinoGrande | 80.8% | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text | 1230 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: instruction following | 1223 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: creative writing | 1174 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: English | 1248 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: non-English | 1205 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: Chinese | 1222 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: Russian | 1228 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: multi-turn | 1222 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: longer queries | 1251 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: writing and language | 1191 | Not measured | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: entertainment and media | 1150 | Not measured | Only Qwen2.5 Coder 32B Instruct 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
Voxtral Small 24B 2507 costs less
Repository review
50K input + 3K output tokens
Voxtral Small 24B 2507 costs less
Agent loop
200K input + 10K output tokens
Voxtral Small 24B 2507 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 | Qwen2.5 Coder 32B Instruct | Mistral Voxtral Small 24B 2507 |
|---|---|---|
| Maker | Qwen | Mistral AI |
| Weights | Open weights | Open weights |
| Released | November 11, 2024 | October 30, 2025 |
| Context window | 33K | 33K |
| Input $/Mtok | $0.66 | $0.10 |
| Output $/Mtok | $1.00 | $0.30 |
| 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 Qwen2.5 Coder 32B Instruct better than Voxtral Small 24B 2507 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, Qwen2.5 Coder 32B Instruct or Voxtral Small 24B 2507?
Qwen2.5 Coder 32B Instruct costs $0.66 per million input tokens and $1.00 per million output tokens; Voxtral Small 24B 2507 costs $0.10 and $0.30. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen2.5 Coder 32B Instruct or Voxtral Small 24B 2507?
Neither: both take 33K tokens.
Has any benchmark tested both Qwen2.5 Coder 32B Instruct and Voxtral Small 24B 2507?
No benchmark has tested both yet. Qwen2.5 Coder 32B Instruct has results on Aider polyglot, SWE-bench Verified and LiveCodeBench (Artificial Analysis run); Voxtral Small 24B 2507 has none yet. Compare them on price and context instead. Data as of October 21, 2026.