DeepSeek V3.1 vs Solar Pro 3
DeepSeek V3.1 leads Solar Pro 3 on the Artificial Analysis Intelligence Index, 13.7 to 7.8, and Solar Pro 3 costs 2.5x less per output token ($0.60 vs $1.50 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
DeepSeek V3.1 or Solar Pro 3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick DeepSeek V3.1 for a larger context window (164K against 131K tokens).
- Shared results
- 1
- DeepSeek V3.1 only
- 10
- Solar Pro 3 only
- 9
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V3.1
DeepSeek V3.1 leads, 13.7 against 7.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Solar Pro 3 has a AA Agentic Index result, 1.4.
Directional only
Web design
Design Arena: websites
No call
Only DeepSeek V3.1 has a Design Arena: websites result, 1122.
Directional only
Long documents
Listed context window
DeepSeek V3.1
DeepSeek V3.1 takes 164K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Solar Pro 3
DeepSeek V3.1 $0.0013, Solar Pro 3 $0.0004 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.1 not benchmarked, Solar Pro 3 not benchmarked.
- Widest category
- Intelligence, 5.9 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: DeepSeek V3.1 13.7 against Solar Pro 3 7.8, 5.9 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.1 $1.50 against Solar Pro 3 $0.60 per million output tokens, 2.5x apart.
- Context window
- DeepSeek V3.1 takes 164K tokens, Solar Pro 3 131K.
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 | Solar Pro 3 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| All shared boards | 1 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards, none shared
| Benchmark | DeepSeek V3.1 | Solar Pro 3 | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 16.2 | Only Solar Pro 3 measured |
| SciCode | Not measured | 25.5% | Only Solar Pro 3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 7.6% | Only Solar Pro 3 measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V3.1 | Solar Pro 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.7 | 7.8 | DeepSeek V3.1 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | DeepSeek V3.1 | Solar Pro 3 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.4 | Only Solar Pro 3 measured |
| τ²-Bench Telecom | Not measured | 86.3% | Only Solar Pro 3 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | DeepSeek V3.1 | Solar Pro 3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 72.4% | Only Solar Pro 3 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 10.3% | Only Solar Pro 3 measured |
| Kagi LLM Benchmark | 53.2% | Not measured | Only DeepSeek V3.1 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 | Solar Pro 3 | 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 | Solar Pro 3 | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | DeepSeek V3.1 | Solar Pro 3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1122 | 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 | 1096 | 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 |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | DeepSeek V3.1 | Solar Pro 3 | Leader |
|---|---|---|---|
| IFBench | Not measured | 71.2% | Only Solar Pro 3 measured |
| Long context reasoning (AA-LCR) | Not measured | 32.3% | Only Solar Pro 3 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 | Solar Pro 3 | 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
Solar Pro 3 costs less
Repository review
50K input + 3K output tokens
Solar Pro 3 costs less
Agent loop
200K input + 10K output tokens
Solar Pro 3 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 | Upstage Solar Pro 3 |
|---|---|---|
| Maker | DeepSeek | Upstage |
| Weights | Open weights | No public weights listed |
| Released | August 21, 2025 | January 27, 2026 |
| Context window | 164K | 131K |
| Input $/Mtok | $0.55 | $0.15 |
| Output $/Mtok | $1.50 | $0.60 |
| 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 Solar Pro 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3.1 for a larger context window (164K against 131K tokens).
Which is cheaper, DeepSeek V3.1 or Solar Pro 3?
DeepSeek V3.1 costs $0.55 per million input tokens and $1.50 per million output tokens; Solar Pro 3 costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3.1 or Solar Pro 3?
DeepSeek V3.1, with 164K tokens against 131K.
How many benchmarks is the DeepSeek V3.1 vs Solar Pro 3 comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.1's coding index rests on 0 independent benchmarks and Solar Pro 3's on 0. Where only one model has a result, the page says so instead of naming a winner.