DeepSeek V3 vs Ling 3.0 Flash VL
Ling 3.0 Flash VL costs 5.3x less per output token than DeepSeek V3 ($0.18 vs $0.9594 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.9594
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.18
DeepSeek V3 or Ling 3.0 Flash VL: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick DeepSeek V3 for a larger context window (164K against 131K tokens).
No benchmark has tested both yet. DeepSeek V3 has results on Aider polyglot, SWE-bench Lite and GPQA Diamond (Epoch AI run); Ling 3.0 Flash VL on AA Coding Index, SciCode and AA Intelligence Index. Compare them on price and context instead.
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 Ling 3.0 Flash VL has a AA Intelligence Index result, 24.6.
Directional only
Agentic work
AA Agentic Index
No call
Only Ling 3.0 Flash VL has a AA Agentic Index result, 28.7.
Directional only
Web design
Design Arena: websites
No call
Only DeepSeek V3 has a Design Arena: websites result, 1120.
Directional only
Long documents
Listed context window
DeepSeek V3
DeepSeek V3 takes 164K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash VL
DeepSeek V3 $0.0008, Ling 3.0 Flash VL $0.0001 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3 not benchmarked, Ling 3.0 Flash VL not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- DeepSeek V3 $0.9594 against Ling 3.0 Flash VL $0.18 per million output tokens, 5.3x apart.
- Context window
- DeepSeek V3 takes 164K tokens, Ling 3.0 Flash VL 131K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards measured
| Benchmark | DeepSeek V3 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| Aider polyglot | 70.2% | Not measured | Only DeepSeek V3 measured |
| SWE-bench Lite | 30.7% | Not measured | Only DeepSeek V3 measured |
| AA Coding Index | Not measured | 57.0 | Only Ling 3.0 Flash VL measured |
| SciCode | Not measured | 44.2% | Only Ling 3.0 Flash VL measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | DeepSeek V3 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 24.6 | Only Ling 3.0 Flash VL 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 measured
| Benchmark | DeepSeek V3 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 28.7 | Only Ling 3.0 Flash VL measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | DeepSeek V3 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 86.2% | Only Ling 3.0 Flash VL measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 22.0% | Only Ling 3.0 Flash VL measured |
| GPQA Diamond (Epoch AI run) | 71.2% | Not measured | Only DeepSeek V3 measured |
| Kagi LLM Benchmark | 52.3% | Not measured | Only DeepSeek V3 measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | DeepSeek V3 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| OTIS Mock AIME | 48.9% | Not measured | Only DeepSeek V3 measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | DeepSeek V3 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| Design Arena: websites | 1120 | Not measured | Only DeepSeek V3 measured |
| Design Arena: UI components | 1090 | Not measured | Only DeepSeek V3 measured |
| Design Arena: game dev | 1053 | Not measured | Only DeepSeek V3 measured |
| Design Arena: data viz | 1089 | Not measured | Only DeepSeek V3 measured |
| Design Arena: 3D | 1086 | Not measured | Only DeepSeek V3 measured |
| Design Arena: all code categories | 1108 | Not measured | Only DeepSeek V3 measured |
| 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 index3 boards measured
| Benchmark | DeepSeek V3 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 78.3% | Only Ling 3.0 Flash VL measured |
| DTBench | 62.7% | Not measured | Only DeepSeek V3 measured |
| LMCA | 15.2% | Not measured | Only DeepSeek V3 measured |
| Neither model has a result on the other 43 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
Ling 3.0 Flash VL costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash VL costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 Flash VL 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 | inclusionAI Ling 3.0 Flash VL |
|---|---|---|
| Maker | DeepSeek | inclusionAI |
| Weights | Open weights | Open weights |
| Released | December 26, 2024 | September 10, 2026 |
| Context window | 164K | 131K |
| Input $/Mtok | $0.2887 | $0.06 |
| Output $/Mtok | $0.9594 | $0.18 |
| 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 better than Ling 3.0 Flash VL for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3 for a larger context window (164K against 131K tokens).
Which is cheaper, DeepSeek V3 or Ling 3.0 Flash VL?
DeepSeek V3 costs $0.2887 per million input tokens and $0.9594 per million output tokens; Ling 3.0 Flash VL costs $0.06 and $0.18. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3 or Ling 3.0 Flash VL?
DeepSeek V3, with 164K tokens against 131K.
Has any benchmark tested both DeepSeek V3 and Ling 3.0 Flash VL?
No benchmark has tested both yet. DeepSeek V3 has results on Aider polyglot, SWE-bench Lite and GPQA Diamond (Epoch AI run); Ling 3.0 Flash VL on AA Coding Index, SciCode and AA Intelligence Index. Compare them on price and context instead. Data as of October 22, 2026.