Qwen2.5 VL 72B Instruct vs Qwen3.7 Max
Qwen2.5 VL 72B Instruct costs 4.4x less per output token than Qwen3.7 Max ($1.00 vs $4.425 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.00
- Coding
- 54.1
- Overall
- 61.7
- Output $/M
- $4.425
Qwen2.5 VL 72B Instruct or Qwen3.7 Max: which to pick
Only Qwen3.7 Max has a coding score, 54.1 on the Vibe Coding Index; Qwen2.5 VL 72B Instruct has none, so the two cannot be ranked on coding.
Pick Qwen2.5 VL 72B Instruct for output tokens 4.4x cheaper ($1.00 vs $4.425 per million).
No benchmark has tested both yet. Qwen2.5 VL 72B Instruct has results on OSWorld, Kagi LLM Benchmark and GeoBench; Qwen3.7 Max on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI). 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 Qwen3.7 Max has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen3.7 Max has a AA Intelligence Index result, 29.5.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.7 Max has a AA Agentic Index result, 22.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.7 Max has a GPQA Diamond result, 90.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.7 Max has a MMLU Pro result, 89.3%.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3.7 Max has a Design Arena: websites result, 1274.
Directional only
Long documents
Listed context window
Qwen3.7 Max
Qwen3.7 Max takes 1M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 VL 72B Instruct
Qwen2.5 VL 72B Instruct $0.0013, Qwen3.7 Max $0.0037 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.7 Max has the number, $4.69.
Directional only
At a glance
- Coding index
- Qwen2.5 VL 72B Instruct not benchmarked, Qwen3.7 Max 54.1 from 3 benchmarks.
- 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 VL 72B Instruct $1.00 against Qwen3.7 Max $4.425 per million output tokens, 4.4x apart.
- Context window
- Qwen2.5 VL 72B Instruct takes 128K tokens, Qwen3.7 Max 1M.
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 Index12 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Qwen3.7 Max | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1515 | Only Qwen3.7 Max measured |
| AA Coding Index | Not measured | 66.0 | Only Qwen3.7 Max measured |
| LiveCodeBench (Vals AI) | Not measured | 87.1% | Only Qwen3.7 Max measured |
| SWE-bench Verified (Vals AI) | Not measured | 68.8% | Only Qwen3.7 Max measured |
| Vibe Code Bench (Vals AI) | Not measured | 47.7% | Only Qwen3.7 Max measured |
| Code migration (Vals AI) | Not measured | 13.1% | Only Qwen3.7 Max measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 61.0% | Only Qwen3.7 Max measured |
| SciCode | Not measured | 49.5% | Only Qwen3.7 Max measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 50.8% | Only Qwen3.7 Max measured |
| ALE-Bench | Not measured | 1189.4 | Only Qwen3.7 Max measured |
| LMArena WebDev: React | Not measured | 1514 | Only Qwen3.7 Max measured |
| LMArena WebDev: HTML | Not measured | 1512 | Only Qwen3.7 Max measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 29.5 | Only Qwen3.7 Max measured |
| Epoch Capabilities Index | Not measured | 154.0 | Only Qwen3.7 Max measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index15 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 22.5 | Only Qwen3.7 Max measured |
| Design Arena: agents building web apps | Not measured | 1208 | Only Qwen3.7 Max measured |
| Design Arena: agents building full-stack apps | Not measured | 1191 | Only Qwen3.7 Max measured |
| Design Arena: agents building mobile apps | Not measured | 1155 | Only Qwen3.7 Max measured |
| Design Arena: agents building Android apps | Not measured | 1159 | Only Qwen3.7 Max measured |
| Design Arena: agents building Godot games | Not measured | 1187 | Only Qwen3.7 Max measured |
| Design Arena: agents building games | Not measured | 1161 | Only Qwen3.7 Max measured |
| Design Arena: HTML slides | Not measured | 1108 | Only Qwen3.7 Max measured |
| Design Arena: PowerPoint slides | Not measured | 1171 | Only Qwen3.7 Max measured |
| Finance Agent (Vals AI) | Not measured | 47.8% | Only Qwen3.7 Max measured |
| Tax Agent Bench (Vals AI) | Not measured | 15.8% | Only Qwen3.7 Max measured |
| Legal Research Bench (Vals AI) | Not measured | 25.5% | Only Qwen3.7 Max measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 57.0% | Only Qwen3.7 Max measured |
| τ²-Bench Telecom | Not measured | 94.7% | Only Qwen3.7 Max measured |
| OSWorld | 5.0% | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 26 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Qwen3.7 Max | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 90.2% | Only Qwen3.7 Max measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.3% | Only Qwen3.7 Max measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 40.5% | Only Qwen3.7 Max measured |
| GPQA Diamond (Epoch AI run) | Not measured | 90.9% | Only Qwen3.7 Max measured |
| SimpleBench | Not measured | 70.4% | Only Qwen3.7 Max measured |
| Chess puzzles | Not measured | 26.0% | Only Qwen3.7 Max measured |
| Mystery game puzzles | Not measured | 32.0% | Only Qwen3.7 Max measured |
| EBR-bench | Not measured | 9.5% | Only Qwen3.7 Max measured |
| Kagi LLM Benchmark | 36.0% | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Qwen3.7 Max | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 95.6% | Only Qwen3.7 Max measured |
| FrontierMath, tiers 1 to 3 | Not measured | 64.6% | Only Qwen3.7 Max measured |
| FrontierMath, tier 4 | Not measured | 34.1% | Only Qwen3.7 Max measured |
| ProofBench | Not measured | 26.0% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Qwen3.7 Max | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 89.3% | Only Qwen3.7 Max measured |
| LegalBench (Vals AI) | Not measured | 84.9% | Only Qwen3.7 Max measured |
| CorpFin (Vals AI) | Not measured | 63.7% | Only Qwen3.7 Max measured |
| TaxEval (Vals AI) | Not measured | 75.3% | Only Qwen3.7 Max measured |
| MedCode (Vals AI) | Not measured | 38.8% | Only Qwen3.7 Max measured |
| SimpleQA Verified | Not measured | 55.8% | Only Qwen3.7 Max measured |
| GeoBench | 62.0% | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Qwen3.7 Max | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1274 | Only Qwen3.7 Max measured |
| Design Arena: UI components | Not measured | 1267 | Only Qwen3.7 Max measured |
| Design Arena: game dev | Not measured | 1264 | Only Qwen3.7 Max measured |
| Design Arena: data viz | Not measured | 1275 | Only Qwen3.7 Max measured |
| Design Arena: 3D | Not measured | 1265 | Only Qwen3.7 Max measured |
| Design Arena: all code categories | Not measured | 1275 | Only Qwen3.7 Max measured |
| Design Arena: SVG | Not measured | 1216 | Only Qwen3.7 Max measured |
| Design Arena: ASCII art | Not measured | 1211 | Only Qwen3.7 Max measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Qwen3.7 Max | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | Not measured | 79.4% | Only Qwen3.7 Max measured |
| IFBench | Not measured | 80.5% | Only Qwen3.7 Max measured |
| Long context reasoning (AA-LCR) | Not measured | 79.0% | Only Qwen3.7 Max measured |
| DTBench | Not measured | 92.3% | Only Qwen3.7 Max measured |
| LMCA | Not measured | 44.0% | Only Qwen3.7 Max measured |
| LMArena Vision | 1107 | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| LMArena Vision: English | 1115 | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| LMArena Vision: Chinese | 1107 | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 38 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 VL 72B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 VL 72B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 VL 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 VL 72B Instruct | Qwen3.7 Max |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | Open weights | No public weights listed |
| Released | February 1, 2025 | May 21, 2026 |
| Context window | 128K | 1M |
| Input $/Mtok | $0.80 | $1.475 |
| Output $/Mtok | $1.00 | $4.425 |
| Coding index | Not benchmarked | 54.1 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $4.69 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen2.5 VL 72B Instruct better than Qwen3.7 Max for coding?
Only Qwen3.7 Max has a coding score, 54.1 on the Vibe Coding Index; Qwen2.5 VL 72B Instruct has none, so the two cannot be ranked on coding. Pick Qwen2.5 VL 72B Instruct for output tokens 4.4x cheaper ($1.00 vs $4.425 per million).
Which is cheaper, Qwen2.5 VL 72B Instruct or Qwen3.7 Max?
Qwen2.5 VL 72B Instruct costs $0.80 per million input tokens and $1.00 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Cost per solved task is known for Qwen3.7 Max only.
Which has the bigger context window, Qwen2.5 VL 72B Instruct or Qwen3.7 Max?
Qwen3.7 Max, with 1M tokens against 128K.
Has any benchmark tested both Qwen2.5 VL 72B Instruct and Qwen3.7 Max?
No benchmark has tested both yet. Qwen2.5 VL 72B Instruct has results on OSWorld, Kagi LLM Benchmark and GeoBench; Qwen3.7 Max on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI). Compare them on price and context instead. Data as of October 22, 2026.