DeepSeek V3.1 vs Step 5 Preview
Step 5 Preview leads DeepSeek V3.1 on the Artificial Analysis Intelligence Index, 43.7 to 13.7, and DeepSeek V3.1 costs 1.8x less per output token ($1.50 vs $2.70 per million). Updated October 21, 2026; 1 benchmarks have a result for both.
DeepSeek V3.1 or Step 5 Preview: which to pick
Only Step 5 Preview has a coding score, 61.1 on the Vibe Coding Index; DeepSeek V3.1 has none, so the two cannot be ranked on coding.
Pick DeepSeek V3.1 for output tokens 1.8x cheaper ($1.50 vs $2.70 per million).
- Shared results
- 1
- DeepSeek V3.1 only
- 10
- Step 5 Preview only
- 60
- Like-for-like categories
- 1 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
Only Step 5 Preview has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Step 5 Preview
Step 5 Preview leads, 43.7 against 13.7.
Same board, both measured
Web design
Design Arena: websites
No call
Only DeepSeek V3.1 has a Design Arena: websites result, 1123.
Directional only
Long documents
Listed context window
Step 5 Preview
Step 5 Preview takes 1.05M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.1
DeepSeek V3.1 $0.0013, Step 5 Preview $0.0024 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.1 not benchmarked, Step 5 Preview 61.1 from 4 benchmarks.
- Widest category
- Intelligence, 30.0 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: DeepSeek V3.1 13.7 against Step 5 Preview 43.7, 30.0 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 $1.50 against Step 5 Preview $2.70 per million output tokens, 1.8x apart.
- Context window
- DeepSeek V3.1 takes 164K tokens, Step 5 Preview 1.05M.
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 5 Preview | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index13 boards, none shared
| Benchmark | DeepSeek V3.1 | Step 5 Preview | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 85.6% | Only Step 5 Preview measured |
| LMArena WebDev | Not measured | 1567 | Only Step 5 Preview measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 31.8% | Only Step 5 Preview measured |
| Vibe Code Bench (Vals AI) | Not measured | 70.4% | Only Step 5 Preview measured |
| Code migration (Vals AI) | Not measured | 39.0% | Only Step 5 Preview measured |
| IOI (Vals AI) | Not measured | 38.1% | Only Step 5 Preview measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 40.8% | Only Step 5 Preview measured |
| SciCode | Not measured | 58.9% | Only Step 5 Preview measured |
| LMArena Text: coding | Not measured | 1485 | Only Step 5 Preview measured |
| LMArena Text: software and IT | Not measured | 1473 | Only Step 5 Preview measured |
| LMArena WebDev: React | Not measured | 1583 | Only Step 5 Preview measured |
| LMArena WebDev: HTML | Not measured | 1556 | Only Step 5 Preview measured |
| LMArena WebDev: from an image | Not measured | 1550 | Only Step 5 Preview measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3.1 | Step 5 Preview | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.7 | 43.7 | Step 5 Preview |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | DeepSeek V3.1 | Step 5 Preview | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 72.8% | Only Step 5 Preview measured |
| LiveBench browser | Not measured | 24.0% | Only Step 5 Preview measured |
| LiveBench long agentic | Not measured | 27.5% | Only Step 5 Preview measured |
| SREBench (Vals AI) | Not measured | 0.4% | Only Step 5 Preview measured |
| Finance Agent (Vals AI) | Not measured | 50.7% | Only Step 5 Preview measured |
| Tax Agent Bench (Vals AI) | Not measured | 27.3% | Only Step 5 Preview measured |
| Legal Research Bench (Vals AI) | Not measured | 40.4% | Only Step 5 Preview measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 57.1% | Only Step 5 Preview measured |
| BioMysteryBench (Vals AI) | Not measured | 67.4% | Only Step 5 Preview measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 2.9% | Only Step 5 Preview measured |
| Vals Science Index | Not measured | 29.6% | Only Step 5 Preview measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V3.1 | Step 5 Preview | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 83.8% | Only Step 5 Preview measured |
| MysteryMechanism (Vals AI) | Not measured | 18.5% | Only Step 5 Preview measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 46.5% | Only Step 5 Preview measured |
| LMArena Text: hard prompts | Not measured | 1461 | Only Step 5 Preview measured |
| LMArena Text: expert | Not measured | 1485 | Only Step 5 Preview measured |
| LMArena Text: hard prompts in English | Not measured | 1454 | Only Step 5 Preview measured |
| LMArena Vision: diagrams | Not measured | 1308 | Only Step 5 Preview measured |
| LMArena Vision: homework | Not measured | 1265 | Only Step 5 Preview measured |
| Kagi LLM Benchmark | 53.2% | Not measured | Only DeepSeek V3.1 measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | DeepSeek V3.1 | Step 5 Preview | Leader |
|---|---|---|---|
| ProofBench | Not measured | 42.0% | Only Step 5 Preview measured |
| LMArena Text: math | Not measured | 1458 | Only Step 5 Preview measured |
| LMArena Text: mathematical work | Not measured | 1460 | Only Step 5 Preview measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | DeepSeek V3.1 | Step 5 Preview | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1454 | Only Step 5 Preview measured |
| LMArena Text: medicine and healthcare | Not measured | 1439 | Only Step 5 Preview measured |
| LMArena Text: legal and government | Not measured | 1437 | Only Step 5 Preview measured |
| LMArena Text: business and finance | Not measured | 1435 | Only Step 5 Preview measured |
| Neither model has a result on the other 14 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V3.1 | Step 5 Preview | Leader |
|---|---|---|---|
| Design Arena: websites | 1123 | Not measured | Only DeepSeek V3.1 measured |
| Design Arena: UI components | 1085 | Not measured | Only DeepSeek V3.1 measured |
| Design Arena: game dev | 1084 | Not measured | Only DeepSeek V3.1 measured |
| Design Arena: data viz | 1095 | Not measured | Only DeepSeek V3.1 measured |
| Design Arena: 3D | 1077 | Not measured | Only DeepSeek V3.1 measured |
| Design Arena: all code categories | 1112 | Not measured | Only DeepSeek V3.1 measured |
| Design Arena: SVG | 967 | Not measured | Only DeepSeek V3.1 measured |
| LiveBench design | Not measured | 76.9% | Only Step 5 Preview measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index22 boards, none shared
| Benchmark | DeepSeek V3.1 | Step 5 Preview | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 63.5% | Only Step 5 Preview measured |
| Public Benefits Bench (Vals AI) | Not measured | 58.1% | Only Step 5 Preview measured |
| Long context reasoning (AA-LCR) | Not measured | 88.3% | Only Step 5 Preview measured |
| DTBench | 82.7% | Not measured | Only DeepSeek V3.1 measured |
| LMCA | 24.3% | Not measured | Only DeepSeek V3.1 measured |
| LMArena Text | Not measured | 1440 | Only Step 5 Preview measured |
| LMArena Text: instruction following | Not measured | 1438 | Only Step 5 Preview measured |
| LMArena Text: creative writing | Not measured | 1409 | Only Step 5 Preview measured |
| LMArena Vision | Not measured | 1265 | Only Step 5 Preview measured |
| LMArena Text: English | Not measured | 1447 | Only Step 5 Preview measured |
| LMArena Text: non-English | Not measured | 1428 | Only Step 5 Preview measured |
| LMArena Text: Chinese | Not measured | 1500 | Only Step 5 Preview measured |
| LMArena Text: Japanese | Not measured | 1383 | Only Step 5 Preview measured |
| LMArena Text: French | Not measured | 1438 | Only Step 5 Preview measured |
| LMArena Text: Spanish | Not measured | 1441 | Only Step 5 Preview measured |
| LMArena Text: Russian | Not measured | 1433 | Only Step 5 Preview measured |
| LMArena Text: multi-turn | Not measured | 1437 | Only Step 5 Preview measured |
| LMArena Text: longer queries | Not measured | 1449 | Only Step 5 Preview measured |
| LMArena Text: writing and language | Not measured | 1425 | Only Step 5 Preview measured |
| LMArena Text: entertainment and media | Not measured | 1412 | Only Step 5 Preview measured |
| LMArena Vision: English | Not measured | 1290 | Only Step 5 Preview measured |
| LMArena Vision: reading text | Not measured | 1282 | Only Step 5 Preview 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 | DeepSeek V3.1 | Step 5 Preview | 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
DeepSeek V3.1 costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.1 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.1 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 5 Preview |
|---|---|---|
| Maker | DeepSeek | StepFun |
| Weights | Open weights | Open weights |
| Released | August 21, 2025 | October 8, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.55 | $1.00 |
| Output $/Mtok | $1.50 | $2.70 |
| Coding index | Not benchmarked | 61.1 |
| Independent measurements behind it | 0 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.1 better than Step 5 Preview for coding?
Only Step 5 Preview has a coding score, 61.1 on the Vibe Coding Index; DeepSeek V3.1 has none, so the two cannot be ranked on coding. Pick DeepSeek V3.1 for output tokens 1.8x cheaper ($1.50 vs $2.70 per million).
Which is cheaper, DeepSeek V3.1 or Step 5 Preview?
DeepSeek V3.1 costs $0.55 per million input tokens and $1.50 per million output tokens; Step 5 Preview costs $1.00 and $2.70. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3.1 or Step 5 Preview?
Step 5 Preview, with 1.05M tokens against 164K.
How many benchmarks is the DeepSeek V3.1 vs Step 5 Preview comparison based on?
1 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 5 Preview's on 4. Where only one model has a result, the page says so instead of naming a winner.