DeepSeek V4 Flash Vision Exp vs Solar Pro 3
DeepSeek V4 Flash Vision Exp leads Solar Pro 3 on the Artificial Analysis Intelligence Index, 34.8 to 7.8, and Solar Pro 3 costs 2.2x less per output token ($0.60 vs $1.32 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
DeepSeek V4 Flash Vision Exp or Solar Pro 3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick DeepSeek V4 Flash Vision Exp for a larger context window (1.05M against 131K tokens).
- Shared results
- 7
- DeepSeek V4 Flash Vision Exp only
- 7
- Solar Pro 3 only
- 3
- Like-for-like categories
- 5 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 V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp leads, 34.8 against 7.8.
Same board, both measured
Agentic work
AA Agentic Index
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp leads, 47.5 against 1.4.
Same board, both measured
Long documents
Listed context window
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Flash Vision Exp takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Solar Pro 3
DeepSeek V4 Flash Vision Exp $0.0011, Solar Pro 3 $0.0004 per turn.
List prices
At a glance
- Coding index
- DeepSeek V4 Flash Vision Exp not benchmarked, Solar Pro 3 not benchmarked.
- Widest category
- General, 49.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): DeepSeek V4 Flash Vision Exp 81.3% against Solar Pro 3 32.3%, 49.0 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4 Flash Vision Exp $1.32 against Solar Pro 3 $0.60 per million output tokens, 2.2x apart.
- Context window
- DeepSeek V4 Flash Vision Exp takes 1.05M 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 V4 Flash Vision Exp | Bars | Solar Pro 3 | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 7 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | DeepSeek V4 Flash Vision Exp | Solar Pro 3 | Leader |
|---|---|---|---|
| LiveBench coding | 37.6% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| AA Coding Index | 65.0 | 16.2 | DeepSeek V4 Flash Vision Exp |
| SciCode | 49.7% | 25.5% | DeepSeek V4 Flash Vision Exp |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 7.6% | Only Solar Pro 3 measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Flash Vision Exp | Solar Pro 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 34.8 | 7.8 | DeepSeek V4 Flash Vision Exp |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Flash Vision Exp | Solar Pro 3 | Leader |
|---|---|---|---|
| AA Agentic Index | 47.5 | 1.4 | DeepSeek V4 Flash Vision Exp |
| LiveBench research | 69.2% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench browser | 64.0% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| LiveBench long agentic | 39.0% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| τ²-Bench Telecom | Not measured | 86.3% | Only Solar Pro 3 measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4 Flash Vision Exp | Solar Pro 3 | Leader |
|---|---|---|---|
| LiveBench reasoning | 85.4% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| GPQA Diamond (Artificial Analysis run) | 91.3% | 72.4% | DeepSeek V4 Flash Vision Exp |
| Humanity's Last Exam (Artificial Analysis run) | 34.5% | 10.3% | DeepSeek V4 Flash Vision Exp |
| 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 V4 Flash Vision Exp | 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 V4 Flash Vision Exp | Solar Pro 3 | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | Solar Pro 3 | Leader |
|---|---|---|---|
| LiveBench design | 70.7% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4 Flash Vision Exp | Solar Pro 3 | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.5% | Not measured | Only DeepSeek V4 Flash Vision Exp measured |
| IFBench | Not measured | 71.2% | Only Solar Pro 3 measured |
| Long context reasoning (AA-LCR) | 81.3% | 32.3% | DeepSeek V4 Flash Vision Exp |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4 Flash Vision Exp | 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 V4 Flash Vision Exp | Upstage Solar Pro 3 |
|---|---|---|
| Maker | DeepSeek | Upstage |
| Weights | Open weights | No public weights listed |
| Released | August 21, 2026 | January 27, 2026 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $0.44 | $0.15 |
| Output $/Mtok | $1.32 | $0.60 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4 Flash Vision Exp better than Solar Pro 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash Vision Exp for a larger context window (1.05M against 131K tokens).
Which is cheaper, DeepSeek V4 Flash Vision Exp or Solar Pro 3?
DeepSeek V4 Flash Vision Exp costs $0.44 per million input tokens and $1.32 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 V4 Flash Vision Exp or Solar Pro 3?
DeepSeek V4 Flash Vision Exp, with 1.05M tokens against 131K.
How many benchmarks is the DeepSeek V4 Flash Vision Exp vs Solar Pro 3 comparison based on?
7 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash Vision Exp's coding index rests on 1 independent benchmark and Solar Pro 3's on 0. Where only one model has a result, the page says so instead of naming a winner.