Qwen3 14B vs Qwen3 Coder Next
Qwen3 Coder Next leads Qwen3 14B on the Artificial Analysis Intelligence Index, 9.2 to 6.7, and Qwen3 14B costs 3.5x less per output token ($0.23 vs $0.80 per million). Updated October 21, 2026; 8 benchmarks have a result for both.
Qwen3 14B or Qwen3 Coder Next: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen3 14B for output tokens 3.5x cheaper ($0.23 vs $0.80 per million) and work measured by SciCode or Terminal-Bench Hard (Artificial Analysis run), where it leads.
- Shared results
- 8
- Qwen3 14B only
- 10
- Qwen3 Coder Next 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
Qwen3 Coder Next
Qwen3 Coder Next leads, 9.2 against 6.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3 Coder Next has a AA Agentic Index result, 0.9.
Directional only
Long documents
Listed context window
Qwen3 Coder Next
Qwen3 Coder Next takes 262K tokens against 41K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 14B
Qwen3 14B $0.0002, Qwen3 Coder Next $0.0005 per turn.
List prices
At a glance
- Coding index
- Qwen3 14B not benchmarked, Qwen3 Coder Next not benchmarked.
- Widest category
- Agentic work, 45.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Qwen3 14B 0.0% against Qwen3 Coder Next 47.0%, 47.0 points apart on a 0 to 100 scale.
- Output price
- Qwen3 14B $0.23 against Qwen3 Coder Next $0.80 per million output tokens, 3.5x apart.
- Context window
- Qwen3 14B takes 41K tokens, Qwen3 Coder Next 262K.
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 | Qwen3 14B | Bars | Qwen3 Coder Next | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| General | 1 | 1 | ||
| All shared boards | 1 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Qwen3 14B | Qwen3 Coder Next | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 36.2 | Only Qwen3 Coder Next measured |
| LiveCodeBench (Artificial Analysis run) | 52.3% | Not measured | Only Qwen3 14B measured |
| SciCode | 30.7% | 36.2% | Qwen3 Coder Next |
| Terminal-Bench Hard (Artificial Analysis run) | 5.3% | 18.2% | Qwen3 Coder Next |
| WeirdML | Not measured | 34.4% | Only Qwen3 Coder Next measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3 14B | Qwen3 Coder Next | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.7 | 9.2 | Qwen3 Coder Next |
| Epoch Capabilities Index | 138.2 | Not measured | Only Qwen3 14B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3 14B | Qwen3 Coder Next | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.9 | Only Qwen3 Coder Next measured |
| τ²-Bench Telecom | 34.5% | 79.5% | Qwen3 Coder Next |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen3 14B | Qwen3 Coder Next | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 60.4% | 73.7% | Qwen3 Coder Next |
| Humanity's Last Exam (Artificial Analysis run) | 4.5% | 10.1% | Qwen3 Coder Next |
| GPQA Diamond (Epoch AI run) | 63.8% | Not measured | Only Qwen3 14B measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Qwen3 14B | Qwen3 Coder Next | Leader |
|---|---|---|---|
| AA Math Index | 58.0 | Not measured | Only Qwen3 14B measured |
| AIME 2025 (Artificial Analysis run) | 58.0% | Not measured | Only Qwen3 14B measured |
| OTIS Mock AIME | 66.4% | Not measured | Only Qwen3 14B measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Qwen3 14B | Qwen3 Coder Next | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 77.4% | Not measured | Only Qwen3 14B measured |
| Neither model has a result on the other 16 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3 14B | Qwen3 Coder Next | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Qwen3 14B | Qwen3 Coder Next | Leader |
|---|---|---|---|
| IFBench | 40.5% | 35.2% | Qwen3 14B |
| Long context reasoning (AA-LCR) | 0.0% | 47.0% | Qwen3 Coder Next |
| DTBench | 64.0% | Not measured | Only Qwen3 14B measured |
| LMCA | 18.2% | Not measured | Only Qwen3 14B measured |
| Fiction.LiveBench | 62.5% | Not measured | Only Qwen3 14B measured |
| Neither model has a result on the other 41 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3 14B | Qwen3 Coder Next | 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
Qwen3 14B costs less
Repository review
50K input + 3K output tokens
Qwen3 14B costs less
Agent loop
200K input + 10K output tokens
Qwen3 14B 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 | Qwen3 14B | Qwen3 Coder Next |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | Open weights | Open weights |
| Released | April 28, 2025 | February 4, 2026 |
| Context window | 41K | 262K |
| Input $/Mtok | $0.11 | $0.12 |
| Output $/Mtok | $0.23 | $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 Qwen3 14B better than Qwen3 Coder Next for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen3 14B for output tokens 3.5x cheaper ($0.23 vs $0.80 per million) and work measured by SciCode or Terminal-Bench Hard (Artificial Analysis run), where it leads.
Which is cheaper, Qwen3 14B or Qwen3 Coder Next?
Qwen3 14B costs $0.11 per million input tokens and $0.23 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, Qwen3 14B or Qwen3 Coder Next?
Qwen3 Coder Next, with 262K tokens against 41K.
How many benchmarks is the Qwen3 14B vs Qwen3 Coder Next comparison based on?
8 benchmarks have a result for both models as of October 21, 2026. Qwen3 14B's coding index rests on 0 independent benchmarks and Qwen3 Coder Next's on 0. Where only one model has a result, the page says so instead of naming a winner.