DeepSeek V3.1 vs Step 3.7 Flash
Updated October 21, 2026. 8 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
DeepSeek V3.1 has the edge where what matters is AA Intelligence Index or Design Arena: websites, where it leads.
- Shared results
- 8
- DeepSeek V3.1 only
- 2
- Step 3.7 Flash only
- 10
- Like-for-like categories
- 2 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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
Step 3.7 Flash
Step 3.7 Flash leads, 19.5 against 13.7.
Same board, both measured
Web design
Design Arena: websites
Step 3.7 Flash
Step 3.7 Flash leads, 1196 against 1123.
Same board, both measured
Long documents
Listed context window
Step 3.7 Flash
Step 3.7 Flash takes 262K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Step 3.7 Flash
DeepSeek V3.1 $0.0013, Step 3.7 Flash $0.0008 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.1 not benchmarked, Step 3.7 Flash not benchmarked.
- Widest category
- Web design, 10.0 points apart on average over 7 shared benchmarks.
- Widest single gap
- Design Arena: SVG: DeepSeek V3.1 967 against Step 3.7 Flash 1085, 14.8 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 $1.50 against Step 3.7 Flash $1.15 per million output tokens, 1.3x apart.
- Context window
- DeepSeek V3.1 takes 164K tokens, Step 3.7 Flash 262K.
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 | DeepSeek V3.1 | Bars | Step 3.7 Flash | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Web design | 0 | 7 | ||
| All shared boards | 0 | 8 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards, none shared
| Benchmark | DeepSeek V3.1 | 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 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 | Step 3.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.7 | 19.5 | Step 3.7 Flash |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | DeepSeek V3.1 | Step 3.7 Flash | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 98.5% | Only Step 3.7 Flash measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | DeepSeek V3.1 | 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 |
| Neither model has a result on the other 19 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 | Step 3.7 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 | Step 3.7 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 17 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V3.1 | Step 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1123 | 1196 | Step 3.7 Flash |
| Design Arena: UI components | 1085 | 1179 | Step 3.7 Flash |
| Design Arena: game dev | 1084 | 1158 | Step 3.7 Flash |
| Design Arena: data viz | 1095 | 1172 | Step 3.7 Flash |
| Design Arena: 3D | 1077 | 1129 | Step 3.7 Flash |
| Design Arena: all code categories | 1112 | 1182 | Step 3.7 Flash |
| Design Arena: SVG | 967 | 1085 | Step 3.7 Flash |
| 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 index4 boards, none shared
| Benchmark | DeepSeek V3.1 | 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 |
| DTBench | 82.7% | Not measured | Only DeepSeek V3.1 measured |
| LMCA | 24.3% | Not measured | Only DeepSeek V3.1 measured |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.1 | Step 3.7 Flash | 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
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 | DeepSeek V3.1 | StepFun Step 3.7 Flash |
|---|---|---|
| Maker | DeepSeek | StepFun |
| Weights | Open weights | Open weights |
| Released | August 21, 2025 | May 28, 2026 |
| Context window | 164K | 262K |
| Input $/Mtok | $0.55 | $0.20 |
| Output $/Mtok | $1.50 | $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 DeepSeek V3.1 better than Step 3.7 Flash for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. DeepSeek V3.1 has the edge where what matters is AA Intelligence Index or Design Arena: websites, where it leads.
Which is cheaper, DeepSeek V3.1 or Step 3.7 Flash?
DeepSeek V3.1 costs $0.55 per million input tokens and $1.50 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, DeepSeek V3.1 or Step 3.7 Flash?
Step 3.7 Flash, with 262K tokens against 164K.
How many benchmarks is the DeepSeek V3.1 vs Step 3.7 Flash comparison based on?
8 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.1's coding index rests on 0 independent benchmarks and Step 3.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.