Qwen2.5 72B Instruct vs Qwen2.5 7B Instruct
Qwen2.5 7B Instruct costs 2.0x less per output token than Qwen2.5 72B Instruct ($0.20 vs $0.40 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
Qwen2.5 72B Instruct or Qwen2.5 7B Instruct: 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.
- Shared results
- 7
- Qwen2.5 72B Instruct only
- 46
- Qwen2.5 7B Instruct only
- 0
- 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
No call
Only Qwen2.5 72B Instruct has a AA Intelligence Index result, 7.7.
Directional only
Long documents
Listed context window
No call
Both take 33K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 7B Instruct
Qwen2.5 72B Instruct $0.0006, Qwen2.5 7B Instruct $0.0002 per turn.
List prices
At a glance
- Coding index
- Qwen2.5 72B Instruct not benchmarked, Qwen2.5 7B Instruct not benchmarked.
- Widest category
- Reasoning, 13.7 points apart on average over 1 shared benchmark.
- Widest single gap
- DTBench: Qwen2.5 72B Instruct 62.9% against Qwen2.5 7B Instruct 47.7%, 15.2 points apart on a 0 to 100 scale.
- Output price
- Qwen2.5 72B Instruct $0.40 against Qwen2.5 7B Instruct $0.20 per million output tokens, 2.0x 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 7B Instruct | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Math | 1 | 0 | ||
| Knowledge | 1 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 7 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards, none shared
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 27.6% | Not measured | Only Qwen2.5 72B Instruct measured |
| 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 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: software and IT | 1292 | Not measured | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.7 | Not measured | Only Qwen2.5 72B Instruct measured |
| Epoch Capabilities Index | 129.0 | 118.5 | Qwen2.5 72B Instruct |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 7B 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% | 7.8% | Qwen2.5 72B Instruct |
| 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 index10
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 49.1% | Not measured | Only Qwen2.5 72B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | 3.6% | Not measured | Only Qwen2.5 72B Instruct measured |
| GPQA Diamond (Epoch AI run) | 49.1% | 35.5% | Qwen2.5 72B Instruct |
| BIG-Bench Hard | 79.8% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts | 1271 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: expert | 1245 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts in English | 1279 | Not measured | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 7B 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% | 2.5% | Qwen2.5 72B Instruct |
| MATH level 5 | 63.2% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: math | 1283 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: mathematical work | 1290 | Not measured | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 72.0% | Not measured | Only Qwen2.5 72B Instruct measured |
| MMLU | 85.3% | 72.9% | Qwen2.5 72B Instruct |
| AI2 Reasoning Challenge | 94.5% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: science | 1275 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: medicine and healthcare | 1258 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: legal and government | 1288 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: business and finance | 1253 | Not measured | Only Qwen2.5 72B Instruct measured |
| 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 7B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Qwen2.5 72B Instruct | Qwen2.5 7B Instruct | Leader |
|---|---|---|---|
| IFBench | 36.9% | Not measured | Only Qwen2.5 72B Instruct measured |
| DTBench | 62.9% | 47.7% | Qwen2.5 72B Instruct |
| LMCA | 13.4% | 6.4% | Qwen2.5 72B Instruct |
| HellaSwag | 84.8% | Not measured | Only Qwen2.5 72B Instruct measured |
| WinoGrande | 82.3% | Not measured | Only Qwen2.5 72B Instruct measured |
| PIQA | 82.6% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text | 1269 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: instruction following | 1254 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: creative writing | 1221 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: English | 1283 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: non-English | 1252 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Chinese | 1273 | Not measured | Only Qwen2.5 72B Instruct measured |
| 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 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: multi-turn | 1272 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: longer queries | 1281 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: writing and language | 1247 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: entertainment and media | 1211 | Not measured | Only Qwen2.5 72B Instruct measured |
| 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 7B 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 7B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 7B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 7B 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 7B Instruct |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | Open weights | Open weights |
| Released | September 19, 2024 | October 16, 2024 |
| Context window | 33K | 33K |
| Input $/Mtok | $0.36 | $0.10 |
| Output $/Mtok | $0.40 | $0.20 |
| 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 7B Instruct 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 72B Instruct or Qwen2.5 7B Instruct?
Qwen2.5 72B Instruct costs $0.36 per million input tokens and $0.40 per million output tokens; Qwen2.5 7B Instruct costs $0.10 and $0.20. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen2.5 72B Instruct or Qwen2.5 7B Instruct?
Neither: both take 33K tokens.
How many benchmarks is the Qwen2.5 72B Instruct vs Qwen2.5 7B Instruct comparison based on?
7 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 7B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.