DeepSeek V3 vs Qwen3 Coder Next
DeepSeek V3 and Qwen3 Coder Next cost about the same per output token ($0.9594 vs $0.80 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.9594
- Coding
- No data
- Overall
- 9.2
- Output $/M
- $0.80
DeepSeek V3 or Qwen3 Coder Next: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. DeepSeek V3 has results on Aider polyglot, SWE-bench Lite and GPQA Diamond (Epoch AI run); Qwen3 Coder Next on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run). 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 Qwen3 Coder Next has a AA Intelligence Index result, 9.2.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3 Coder Next has a AA Agentic Index result, 0.9.
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
Qwen3 Coder Next
Qwen3 Coder Next takes 262K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 Coder Next
DeepSeek V3 $0.0008, Qwen3 Coder Next $0.0005 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3 not benchmarked, Qwen3 Coder Next 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 Qwen3 Coder Next $0.80 per million output tokens, 1.2x apart.
- Context window
- DeepSeek V3 takes 164K tokens, Qwen3 Coder Next 262K.
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 Index6 boards measured
| Benchmark | DeepSeek V3 | Qwen3 Coder Next | 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 | 36.2 | Only Qwen3 Coder Next measured |
| SciCode | Not measured | 36.2% | Only Qwen3 Coder Next measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 18.2% | Only Qwen3 Coder Next measured |
| WeirdML | Not measured | 34.4% | Only Qwen3 Coder Next measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | DeepSeek V3 | Qwen3 Coder Next | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 9.2 | Only Qwen3 Coder Next measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | DeepSeek V3 | Qwen3 Coder Next | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.9 | Only Qwen3 Coder Next measured |
| τ²-Bench Telecom | Not measured | 79.5% | Only Qwen3 Coder Next measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | DeepSeek V3 | Qwen3 Coder Next | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 73.7% | Only Qwen3 Coder Next measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 10.1% | Only Qwen3 Coder Next measured |
| GPQA Diamond (Epoch AI run) | 71.2% | 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 | Qwen3 Coder Next | 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 | Qwen3 Coder Next | Leader |
|---|---|---|---|
| Design Arena: websites | 1120 | Not measured | Only DeepSeek V3 measured |
| Design Arena: UI components | 1093 | 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 | 1087 | 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 index4 boards measured
| Benchmark | DeepSeek V3 | Qwen3 Coder Next | Leader |
|---|---|---|---|
| IFBench | Not measured | 35.2% | Only Qwen3 Coder Next measured |
| Long context reasoning (AA-LCR) | Not measured | 47.0% | Only Qwen3 Coder Next 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 42 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
Qwen3 Coder Next costs less
Repository review
50K input + 3K output tokens
Qwen3 Coder Next costs less
Agent loop
200K input + 10K output tokens
Qwen3 Coder Next 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 | Qwen3 Coder Next |
|---|---|---|
| Maker | DeepSeek | Qwen |
| Weights | Open weights | Open weights |
| Released | December 26, 2024 | February 4, 2026 |
| Context window | 164K | 262K |
| Input $/Mtok | $0.2887 | $0.12 |
| Output $/Mtok | $0.9594 | $0.80 |
| 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 Qwen3 Coder Next for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, DeepSeek V3 or Qwen3 Coder Next?
DeepSeek V3 costs $0.2887 per million input tokens and $0.9594 per million output tokens; Qwen3 Coder Next costs $0.12 and $0.80. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V3 or Qwen3 Coder Next?
Qwen3 Coder Next, with 262K tokens against 164K.
Has any benchmark tested both DeepSeek V3 and Qwen3 Coder Next?
No benchmark has tested both yet. DeepSeek V3 has results on Aider polyglot, SWE-bench Lite and GPQA Diamond (Epoch AI run); Qwen3 Coder Next on AA Coding Index, SciCode and Terminal-Bench Hard (Artificial Analysis run). Compare them on price and context instead. Data as of October 21, 2026.