Qwen2.5 VL 72B Instruct vs Extract
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
- No data
Qwen2.5 VL 72B Instruct or Extract: 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 VL 72B Instruct has results on OSWorld, Kagi LLM Benchmark and GeoBench; Extract 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
Long documents
Listed context window
Extract
Extract takes 1M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Extract
Qwen2.5 VL 72B Instruct $0.0013, Extract $0.0000 per turn.
List prices
At a glance
- Coding index
- Qwen2.5 VL 72B Instruct not benchmarked, Extract 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 VL 72B Instruct $1.00 against Extract Free per million output tokens.
- Context window
- Qwen2.5 VL 72B Instruct takes 128K tokens, Extract 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.
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen2.5 VL 72B Instruct | Extract | Leader |
|---|---|---|---|
| OSWorld | 5.0% | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen2.5 VL 72B Instruct | Extract | Leader |
|---|---|---|---|
| Kagi LLM Benchmark | 36.0% | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 21 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen2.5 VL 72B Instruct | Extract | Leader |
|---|---|---|---|
| GeoBench | 62.0% | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 17 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Extract | Leader |
|---|---|---|---|
| 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 43 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
Extract costs less
Repository review
50K input + 3K output tokens
Extract costs less
Agent loop
200K input + 10K output tokens
Extract 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 | ScaleDown Extract |
|---|---|---|
| Maker | Qwen | Scaledown |
| Weights | Open weights | No public weights listed |
| Released | February 1, 2025 | October 13, 2026 |
| Context window | 128K | 1M |
| Input $/Mtok | $0.80 | $0.04 |
| Output $/Mtok | $1.00 | Free |
| 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 VL 72B Instruct better than Extract 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 VL 72B Instruct or Extract?
Qwen2.5 VL 72B Instruct costs $0.80 per million input tokens and $1.00 per million output tokens; Extract costs $0.04 and Free. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen2.5 VL 72B Instruct or Extract?
Extract, with 1M tokens against 128K.
Has any benchmark tested both Qwen2.5 VL 72B Instruct and Extract?
No benchmark has tested both yet. Qwen2.5 VL 72B Instruct has results on OSWorld, Kagi LLM Benchmark and GeoBench; Extract has none yet. Compare them on price and context instead. Data as of October 21, 2026.