Qwen2.5 VL 72B Instruct vs Step 3.7 Flash
Qwen2.5 VL 72B Instruct and Step 3.7 Flash cost about the same per output token ($1.00 vs $1.15 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
- $1.15
Qwen2.5 VL 72B Instruct or Step 3.7 Flash: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen2.5 VL 72B Instruct for output tokens 1.1x cheaper ($1.00 vs $1.15 per million).
No benchmark has tested both yet. Qwen2.5 VL 72B Instruct has results on OSWorld, Kagi LLM Benchmark and GeoBench; Step 3.7 Flash on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run). 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 Step 3.7 Flash has a AA Intelligence Index result, 19.5.
Directional only
Web design
Design Arena: websites
No call
Only Step 3.7 Flash has a Design Arena: websites result, 1196.
Directional only
Long documents
Listed context window
Step 3.7 Flash
Step 3.7 Flash takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Step 3.7 Flash
Qwen2.5 VL 72B Instruct $0.0013, Step 3.7 Flash $0.0008 per turn.
List prices
At a glance
- Coding index
- Qwen2.5 VL 72B Instruct not benchmarked, Step 3.7 Flash 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 Step 3.7 Flash $1.15 per million output tokens, 1.1x apart.
- Context window
- Qwen2.5 VL 72B Instruct takes 128K tokens, Step 3.7 Flash 262K.
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 Index4 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Step 3.7 Flash | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 39.6 | Only Step 3.7 Flash measured |
| SciCode | Not measured | 43.9% | Only Step 3.7 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 35.6% | Only Step 3.7 Flash measured |
| ALE-Bench | Not measured | 694.1 | Only Step 3.7 Flash measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen2.5 VL 72B Instruct | Step 3.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 19.5 | Only Step 3.7 Flash measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Step 3.7 Flash | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 98.5% | Only Step 3.7 Flash measured |
| OSWorld | 5.0% | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Step 3.7 Flash | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 80.9% | Only Step 3.7 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 21.4% | Only Step 3.7 Flash measured |
| Kagi LLM Benchmark | 36.0% | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 19 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen2.5 VL 72B Instruct | Step 3.7 Flash | Leader |
|---|---|---|---|
| GeoBench | 62.0% | Not measured | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 17 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Step 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1196 | Only Step 3.7 Flash measured |
| Design Arena: UI components | Not measured | 1179 | Only Step 3.7 Flash measured |
| Design Arena: game dev | Not measured | 1158 | Only Step 3.7 Flash measured |
| Design Arena: data viz | Not measured | 1172 | Only Step 3.7 Flash measured |
| Design Arena: 3D | Not measured | 1129 | Only Step 3.7 Flash measured |
| Design Arena: all code categories | Not measured | 1182 | Only Step 3.7 Flash measured |
| Design Arena: SVG | Not measured | 1085 | Only Step 3.7 Flash measured |
| Design Arena: ASCII art | Not measured | 1152 | Only Step 3.7 Flash measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Qwen2.5 VL 72B Instruct | Step 3.7 Flash | Leader |
|---|---|---|---|
| IFBench | Not measured | 67.3% | Only Step 3.7 Flash measured |
| Long context reasoning (AA-LCR) | Not measured | 73.7% | Only Step 3.7 Flash 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 41 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
Step 3.7 Flash costs less
Repository review
50K input + 3K output tokens
Step 3.7 Flash costs less
Agent loop
200K input + 10K output tokens
Step 3.7 Flash 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 | StepFun Step 3.7 Flash |
|---|---|---|
| Maker | Qwen | StepFun |
| Weights | Open weights | Open weights |
| Released | February 1, 2025 | May 28, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $0.80 | $0.20 |
| Output $/Mtok | $1.00 | $1.15 |
| 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 Step 3.7 Flash for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen2.5 VL 72B Instruct for output tokens 1.1x cheaper ($1.00 vs $1.15 per million).
Which is cheaper, Qwen2.5 VL 72B Instruct or Step 3.7 Flash?
Qwen2.5 VL 72B Instruct costs $0.80 per million input tokens and $1.00 per million output tokens; Step 3.7 Flash costs $0.20 and $1.15. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen2.5 VL 72B Instruct or Step 3.7 Flash?
Step 3.7 Flash, with 262K tokens against 128K.
Has any benchmark tested both Qwen2.5 VL 72B Instruct and Step 3.7 Flash?
No benchmark has tested both yet. Qwen2.5 VL 72B Instruct has results on OSWorld, Kagi LLM Benchmark and GeoBench; Step 3.7 Flash on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run). Compare them on price and context instead. Data as of October 21, 2026.