Qwen2.5 72B Instruct vs Qwen2.5 Coder 32B Instruct
Qwen2.5 72B Instruct leads Qwen2.5 Coder 32B Instruct on the Artificial Analysis Intelligence Index, 7.7 to 6.7, and Qwen2.5 72B Instruct costs 2.5x less per output token ($0.40 vs $1.00 per million). Updated October 22, 2026; 32 benchmarks have a result for both.
Qwen2.5 72B Instruct or Qwen2.5 Coder 32B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen2.5 72B Instruct for output tokens 2.5x cheaper ($0.40 vs $1.00 per million) and work measured by LiveCodeBench (Artificial Analysis run), where it leads.
- Shared results
- 32
- Qwen2.5 72B Instruct only
- 21
- Qwen2.5 Coder 32B Instruct only
- 3
- Like-for-like categories
- 6 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
Qwen2.5 72B Instruct
Qwen2.5 72B Instruct leads, 7.7 against 6.7.
Same board, both measured
Long documents
Listed context window
No call
Both take 33K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 72B Instruct
Qwen2.5 72B Instruct $0.0006, Qwen2.5 Coder 32B Instruct $0.0012 per turn.
List prices
At a glance
- Coding index
- Qwen2.5 72B Instruct not benchmarked, Qwen2.5 Coder 32B Instruct not benchmarked.
- Widest category
- Knowledge, 9.9 points apart on average over 7 shared benchmarks.
- Widest single gap
- AI2 Reasoning Challenge: Qwen2.5 72B Instruct 94.5% against Qwen2.5 Coder 32B Instruct 70.5%, 24.0 points apart on a 0 to 100 scale.
- Output price
- Qwen2.5 72B Instruct $0.40 against Qwen2.5 Coder 32B Instruct $1.00 per million output tokens, 2.5x apart.
- Context window
- Both take 33K tokens.
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 | Qwen2.5 72B Instruct | Bars | Qwen2.5 Coder 32B Instruct | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 7 | 0 | ||
| General | 13 | 0 | ||
| All shared boards | 31 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 16.4% | Only Qwen2.5 Coder 32B Instruct measured |
| SWE-bench Verified | Not measured | 47.0% | Only Qwen2.5 Coder 32B Instruct measured |
| LiveCodeBench (Artificial Analysis run) | 27.6% | 29.5% | Qwen2.5 Coder 32B Instruct |
| Terminal-Bench Hard (Artificial Analysis run) | 4.5% | Not measured | Only Qwen2.5 72B Instruct measured |
| WeirdML | 16.0% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: coding | 1292 | 1276 | Qwen2.5 72B Instruct |
| LMArena Text: software and IT | 1292 | 1261 | Qwen2.5 72B Instruct |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.7 | 6.7 | Qwen2.5 72B Instruct |
| Epoch Capabilities Index | 129.0 | 119.5 | Qwen2.5 72B Instruct |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 34.5% | Not measured | Only Qwen2.5 72B Instruct measured |
| METR time horizons | 35.8% | Not measured | Only Qwen2.5 72B Instruct measured |
| BALROG | 16.2% | Not measured | Only Qwen2.5 72B Instruct measured |
| TheAgentCompany | 5.7% | Not measured | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 49.1% | 41.7% | Qwen2.5 72B Instruct |
| Humanity's Last Exam (Artificial Analysis run) | 3.6% | 3.5% | Qwen2.5 72B Instruct |
| GPQA Diamond (Epoch AI run) | 49.1% | Not measured | Only Qwen2.5 72B Instruct measured |
| BIG-Bench Hard | 79.8% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts | 1271 | 1251 | Qwen2.5 72B Instruct |
| LMArena Text: expert | 1245 | 1221 | Qwen2.5 72B Instruct |
| LMArena Text: hard prompts in English | 1279 | 1269 | Qwen2.5 72B Instruct |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| AA Math Index | 14.0 | Not measured | Only Qwen2.5 72B Instruct measured |
| AIME 2025 (Artificial Analysis run) | 14.0% | Not measured | Only Qwen2.5 72B Instruct measured |
| OTIS Mock AIME | 8.1% | Not measured | Only Qwen2.5 72B Instruct measured |
| MATH level 5 | 63.2% | Not measured | Only Qwen2.5 72B Instruct measured |
| GSM8K | Not measured | 93.0% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: math | 1283 | 1251 | Qwen2.5 72B Instruct |
| LMArena Text: mathematical work | 1290 | 1243 | Qwen2.5 72B Instruct |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 72.0% | 63.5% | Qwen2.5 72B Instruct |
| MMLU | 85.3% | 79.1% | Qwen2.5 72B Instruct |
| AI2 Reasoning Challenge | 94.5% | 70.5% | Qwen2.5 72B Instruct |
| LMArena Text: science | 1275 | 1221 | Qwen2.5 72B Instruct |
| LMArena Text: medicine and healthcare | 1258 | 1187 | Qwen2.5 72B Instruct |
| LMArena Text: legal and government | 1288 | 1257 | Qwen2.5 72B Instruct |
| LMArena Text: business and finance | 1253 | 1224 | Qwen2.5 72B Instruct |
| Neither model has a result on the other 11 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index130
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| IFBench | 36.9% | Not measured | Only Qwen2.5 72B Instruct measured |
| DTBench | 62.9% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMCA | 13.4% | Not measured | Only Qwen2.5 72B Instruct measured |
| HellaSwag | 84.8% | 83.0% | Qwen2.5 72B Instruct |
| WinoGrande | 82.3% | 80.8% | Qwen2.5 72B Instruct |
| PIQA | 82.6% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text | 1269 | 1230 | Qwen2.5 72B Instruct |
| LMArena Text: instruction following | 1254 | 1223 | Qwen2.5 72B Instruct |
| LMArena Text: creative writing | 1221 | 1174 | Qwen2.5 72B Instruct |
| LMArena Text: English | 1283 | 1248 | Qwen2.5 72B Instruct |
| LMArena Text: non-English | 1252 | 1205 | Qwen2.5 72B Instruct |
| LMArena Text: Chinese | 1273 | 1222 | Qwen2.5 72B Instruct |
| LMArena Text: German | 1234 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Japanese | 1180 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Korean | 1188 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: French | 1280 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Spanish | 1255 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Russian | 1264 | 1228 | Qwen2.5 72B Instruct |
| LMArena Text: multi-turn | 1272 | 1222 | Qwen2.5 72B Instruct |
| LMArena Text: longer queries | 1281 | 1251 | Qwen2.5 72B Instruct |
| LMArena Text: writing and language | 1247 | 1191 | Qwen2.5 72B Instruct |
| LMArena Text: entertainment and media | 1211 | 1150 | Qwen2.5 72B Instruct |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 Coder 32B Instruct | 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
Qwen2.5 72B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 72B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 72B Instruct 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 72B Instruct | Qwen2.5 Coder 32B Instruct |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | Open weights | Open weights |
| Released | September 19, 2024 | November 11, 2024 |
| Context window | 33K | 33K |
| Input $/Mtok | $0.36 | $0.66 |
| Output $/Mtok | $0.40 | $1.00 |
| 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 72B Instruct better than Qwen2.5 Coder 32B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen2.5 72B Instruct for output tokens 2.5x cheaper ($0.40 vs $1.00 per million) and work measured by LiveCodeBench (Artificial Analysis run), where it leads.
Which is cheaper, Qwen2.5 72B Instruct or Qwen2.5 Coder 32B Instruct?
Qwen2.5 72B Instruct costs $0.36 per million input tokens and $0.40 per million output tokens; Qwen2.5 Coder 32B Instruct costs $0.66 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen2.5 72B Instruct or Qwen2.5 Coder 32B Instruct?
Neither: both take 33K tokens.
How many benchmarks is the Qwen2.5 72B Instruct vs Qwen2.5 Coder 32B Instruct comparison based on?
32 benchmarks have a result for both models as of October 22, 2026. Qwen2.5 72B Instruct's coding index rests on 0 independent benchmarks and Qwen2.5 Coder 32B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.