DeepSeek V3 vs Solar Pro 4
Solar Pro 4 costs 1.6x less per output token than DeepSeek V3 ($0.60 vs $0.9594 per million). Updated October 22, 2026; 6 benchmarks have a result for both.
DeepSeek V3 or Solar Pro 4: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick DeepSeek V3 for work measured by Design Arena: websites or Design Arena: UI components, where it leads.
- Shared results
- 6
- DeepSeek V3 only
- 8
- Solar Pro 4 only
- 39
- 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
No call
Only Solar Pro 4 has a AA Intelligence Index result, 28.2.
Directional only
Web design
Design Arena: websites
Solar Pro 4
Solar Pro 4 leads, 1176 against 1120.
Same board, both measured
Long documents
Listed context window
Solar Pro 4
Solar Pro 4 takes 524K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Solar Pro 4
DeepSeek V3 $0.0008, Solar Pro 4 $0.0004 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3 not benchmarked, Solar Pro 4 not benchmarked.
- Widest category
- Web design, 10.1 points apart on average over 6 shared benchmarks.
- Widest single gap
- Design Arena: game dev: DeepSeek V3 1053 against Solar Pro 4 1169, 14.5 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 $0.9594 against Solar Pro 4 $0.60 per million output tokens, 1.6x apart.
- Context window
- DeepSeek V3 takes 164K tokens, Solar Pro 4 524K.
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 | Bars | Solar Pro 4 | Ties |
|---|---|---|---|---|
| Web design | 0 | 6 | ||
| All shared boards | 0 | 6 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index10 boards, none shared
| Benchmark | DeepSeek V3 | Solar Pro 4 | Leader |
|---|---|---|---|
| Aider polyglot | 70.2% | Not measured | Only DeepSeek V3 measured |
| SWE-bench Lite | 30.7% | Not measured | Only DeepSeek V3 measured |
| LMArena WebDev | Not measured | 1371 | Only Solar Pro 4 measured |
| AA Coding Index | Not measured | 52.7 | Only Solar Pro 4 measured |
| SciCode | Not measured | 48.0% | Only Solar Pro 4 measured |
| ALE-Bench | Not measured | 179.3 | Only Solar Pro 4 measured |
| LMArena Text: coding | Not measured | 1438 | Only Solar Pro 4 measured |
| LMArena Text: software and IT | Not measured | 1431 | Only Solar Pro 4 measured |
| LMArena WebDev: React | Not measured | 1363 | Only Solar Pro 4 measured |
| LMArena WebDev: HTML | Not measured | 1371 | Only Solar Pro 4 measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | DeepSeek V3 | Solar Pro 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 28.2 | Only Solar Pro 4 measured |
| 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 | Solar Pro 4 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1105 | Only Solar Pro 4 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | DeepSeek V3 | Solar Pro 4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.1% | Only Solar Pro 4 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 29.8% | Only Solar Pro 4 measured |
| GPQA Diamond (Epoch AI run) | 71.2% | Not measured | Only DeepSeek V3 measured |
| LMArena Text: hard prompts | Not measured | 1400 | Only Solar Pro 4 measured |
| LMArena Text: expert | Not measured | 1428 | Only Solar Pro 4 measured |
| LMArena Text: hard prompts in English | Not measured | 1427 | Only Solar Pro 4 measured |
| Kagi LLM Benchmark | 52.3% | Not measured | Only DeepSeek V3 measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | DeepSeek V3 | Solar Pro 4 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 48.9% | Not measured | Only DeepSeek V3 measured |
| LMArena Text: math | Not measured | 1421 | Only Solar Pro 4 measured |
| LMArena Text: mathematical work | Not measured | 1427 | Only Solar Pro 4 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 | Solar Pro 4 | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1404 | Only Solar Pro 4 measured |
| LMArena Text: medicine and healthcare | Not measured | 1374 | Only Solar Pro 4 measured |
| LMArena Text: legal and government | Not measured | 1383 | Only Solar Pro 4 measured |
| LMArena Text: business and finance | Not measured | 1381 | Only Solar Pro 4 measured |
| Neither model has a result on the other 14 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | DeepSeek V3 | Solar Pro 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1120 | 1176 | Solar Pro 4 |
| Design Arena: UI components | 1090 | 1147 | Solar Pro 4 |
| Design Arena: game dev | 1053 | 1169 | Solar Pro 4 |
| Design Arena: data viz | 1089 | 1177 | Solar Pro 4 |
| Design Arena: 3D | 1086 | 1178 | Solar Pro 4 |
| Design Arena: all code categories | 1108 | 1182 | Solar Pro 4 |
| Design Arena: SVG | 976 | Not measured | Only DeepSeek V3 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
| Benchmark | DeepSeek V3 | Solar Pro 4 | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 70.7% | Only Solar Pro 4 measured |
| DTBench | 62.7% | Not measured | Only DeepSeek V3 measured |
| LMCA | 15.2% | Not measured | Only DeepSeek V3 measured |
| LMArena Text | Not measured | 1388 | Only Solar Pro 4 measured |
| LMArena Text: instruction following | Not measured | 1375 | Only Solar Pro 4 measured |
| LMArena Text: creative writing | Not measured | 1317 | Only Solar Pro 4 measured |
| LMArena Text: English | Not measured | 1414 | Only Solar Pro 4 measured |
| LMArena Text: non-English | Not measured | 1363 | Only Solar Pro 4 measured |
| LMArena Text: Chinese | Not measured | 1422 | Only Solar Pro 4 measured |
| LMArena Text: German | Not measured | 1358 | Only Solar Pro 4 measured |
| LMArena Text: Japanese | Not measured | 1320 | Only Solar Pro 4 measured |
| LMArena Text: Korean | Not measured | 1383 | Only Solar Pro 4 measured |
| LMArena Text: French | Not measured | 1400 | Only Solar Pro 4 measured |
| LMArena Text: Spanish | Not measured | 1409 | Only Solar Pro 4 measured |
| LMArena Text: Russian | Not measured | 1357 | Only Solar Pro 4 measured |
| LMArena Text: Polish | Not measured | 1304 | Only Solar Pro 4 measured |
| LMArena Text: multi-turn | Not measured | 1385 | Only Solar Pro 4 measured |
| LMArena Text: longer queries | Not measured | 1382 | Only Solar Pro 4 measured |
| LMArena Text: writing and language | Not measured | 1344 | Only Solar Pro 4 measured |
| LMArena Text: entertainment and media | Not measured | 1332 | Only Solar Pro 4 measured |
| Neither model has a result on the other 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 | Solar Pro 4 | 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 4 costs less
Repository review
50K input + 3K output tokens
Solar Pro 4 costs less
Agent loop
200K input + 10K output tokens
Solar Pro 4 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 | Upstage Solar Pro 4 |
|---|---|---|
| Maker | DeepSeek | Upstage |
| Weights | Open weights | No public weights listed |
| Released | December 26, 2024 | August 10, 2026 |
| Context window | 164K | 524K |
| Input $/Mtok | $0.2887 | $0.15 |
| Output $/Mtok | $0.9594 | $0.60 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 better than Solar Pro 4 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3 for work measured by Design Arena: websites or Design Arena: UI components, where it leads.
Which is cheaper, DeepSeek V3 or Solar Pro 4?
DeepSeek V3 costs $0.2887 per million input tokens and $0.9594 per million output tokens; Solar Pro 4 costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3 or Solar Pro 4?
Solar Pro 4, with 524K tokens against 164K.
How many benchmarks is the DeepSeek V3 vs Solar Pro 4 comparison based on?
6 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3's coding index rests on 0 independent benchmarks and Solar Pro 4's on 1. Where only one model has a result, the page says so instead of naming a winner.