GPT-5.4 Nano vs Qwen3 14B
GPT-5.4 Nano leads Qwen3 14B on the Artificial Analysis Intelligence Index, 20.7 to 6.7, and Qwen3 14B costs 5.4x less per output token ($0.23 vs $1.25 per million). Updated October 22, 2026; 14 benchmarks have a result for both.
GPT-5.4 Nano or Qwen3 14B: which to pick
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; Qwen3 14B has none, so the two cannot be ranked on coding.
Pick Qwen3 14B for output tokens 5.4x cheaper ($0.23 vs $1.25 per million) and work measured by Kagi LLM Benchmark, where it leads.
- Shared results
- 14
- GPT-5.4 Nano only
- 71
- Qwen3 14B only
- 6
- Like-for-like categories
- 6 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
Only GPT-5.4 Nano has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.4 Nano
GPT-5.4 Nano leads, 20.7 against 6.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.4 Nano has a AA Agentic Index result, 16.0.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.4 Nano has a GPQA Diamond result, 77.5%.
Directional only
Math
AIME
No call
Only GPT-5.4 Nano has a AIME result, 88.8%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 Nano has a MMLU Pro result, 77.2%.
Directional only
Long documents
Listed context window
GPT-5.4 Nano
GPT-5.4 Nano takes 400K tokens against 41K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3 14B
GPT-5.4 Nano $0.0008, Qwen3 14B $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.4 Nano has the number, $0.14.
Directional only
At a glance
- Coding index
- GPT-5.4 Nano 44.8 from 2 benchmarks, Qwen3 14B not benchmarked.
- Widest category
- Agentic work, 41.5 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): GPT-5.4 Nano 76.7% against Qwen3 14B 0.0%, 76.7 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Nano $1.25 against Qwen3 14B $0.23 per million output tokens, 5.4x apart.
- Context window
- GPT-5.4 Nano takes 400K tokens, Qwen3 14B 41K.
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 | GPT-5.4 Nano | Bars | Qwen3 14B | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 3 | 1 | ||
| Math | 1 | 0 | ||
| General | 4 | 0 | ||
| All shared boards | 13 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | GPT-5.4 Nano | Qwen3 14B | Leader |
|---|---|---|---|
| AA Coding Index | 56.1 | Not measured | Only GPT-5.4 Nano measured |
| LiveCodeBench (Vals AI) | 84.0% | Not measured | Only GPT-5.4 Nano measured |
| SWE-bench Verified (Vals AI) | 69.8% | Not measured | Only GPT-5.4 Nano measured |
| Vibe Code Bench (Vals AI) | 26.1% | Not measured | Only GPT-5.4 Nano measured |
| Code migration (Vals AI) | 14.5% | Not measured | Only GPT-5.4 Nano measured |
| Terminal-Bench 2.1 (Vals AI) | 41.6% | Not measured | Only GPT-5.4 Nano measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 52.3% | Only Qwen3 14B measured |
| SciCode | 47.2% | 30.7% | GPT-5.4 Nano |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | 5.3% | GPT-5.4 Nano |
| WeirdML | 49.2% | Not measured | Only GPT-5.4 Nano measured |
| ALE-Bench | 1004.5 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: coding | 1404 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: software and IT | 1402 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 Nano | Qwen3 14B | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.7 | 6.7 | GPT-5.4 Nano |
| Epoch Capabilities Index | 146.0 | 138.2 | GPT-5.4 Nano |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 Nano | Qwen3 14B | Leader |
|---|---|---|---|
| AA Agentic Index | 16.0 | Not measured | Only GPT-5.4 Nano measured |
| Finance Agent (Vals AI) | 38.2% | Not measured | Only GPT-5.4 Nano measured |
| Tax Agent Bench (Vals AI) | 5.0% | Not measured | Only GPT-5.4 Nano measured |
| Legal Research Bench (Vals AI) | 6.3% | Not measured | Only GPT-5.4 Nano measured |
| Excel Modeling Benchmark (Vals AI) | 44.8% | Not measured | Only GPT-5.4 Nano measured |
| τ²-Bench Telecom | 76.0% | 34.5% | GPT-5.4 Nano |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 41.0% | Only Qwen3 14B measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | GPT-5.4 Nano | Qwen3 14B | Leader |
|---|---|---|---|
| GPQA Diamond | 77.5% | Not measured | Only GPT-5.4 Nano measured |
| MMMU Pro (Vals AI) | 73.6% | Not measured | Only GPT-5.4 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 81.7% | 60.4% | GPT-5.4 Nano |
| Humanity's Last Exam (Artificial Analysis run) | 28.3% | 4.5% | GPT-5.4 Nano |
| GPQA Diamond (Epoch AI run) | 78.5% | 63.8% | GPT-5.4 Nano |
| ARC-AGI | 51.5% | Not measured | Only GPT-5.4 Nano measured |
| ARC-AGI-2 | 5.7% | Not measured | Only GPT-5.4 Nano measured |
| Chess puzzles | 45.0% | Not measured | Only GPT-5.4 Nano measured |
| Mystery game puzzles | 9.0% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: hard prompts | 1381 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: expert | 1396 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: hard prompts in English | 1387 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: diagrams | 1210 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: homework | 1225 | Not measured | Only GPT-5.4 Nano measured |
| Kagi LLM Benchmark | 39.7% | 49.1% | Qwen3 14B |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 Nano | Qwen3 14B | Leader |
|---|---|---|---|
| AIME | 88.8% | Not measured | Only GPT-5.4 Nano measured |
| AA Math Index | Not measured | 58.0 | Only Qwen3 14B measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 58.0% | Only Qwen3 14B measured |
| OTIS Mock AIME | 87.8% | 66.4% | GPT-5.4 Nano |
| FrontierMath, tiers 1 to 3 | 44.9% | Not measured | Only GPT-5.4 Nano measured |
| FrontierMath, tier 4 | 12.2% | Not measured | Only GPT-5.4 Nano measured |
| ProofBench | 5.0% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: math | 1405 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: mathematical work | 1409 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | GPT-5.4 Nano | Qwen3 14B | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | Not measured | Only GPT-5.4 Nano measured |
| LegalBench (Vals AI) | 77.9% | Not measured | Only GPT-5.4 Nano measured |
| CaseLaw (Vals AI) | 51.9% | Not measured | Only GPT-5.4 Nano measured |
| CorpFin (Vals AI) | 61.2% | Not measured | Only GPT-5.4 Nano measured |
| TaxEval (Vals AI) | 67.4% | Not measured | Only GPT-5.4 Nano measured |
| MortgageTax (Vals AI) | 59.1% | Not measured | Only GPT-5.4 Nano measured |
| MedCode (Vals AI) | 41.0% | Not measured | Only GPT-5.4 Nano measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 77.4% | Only Qwen3 14B measured |
| SimpleQA Verified | 11.7% | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: science | 1374 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: medicine and healthcare | 1369 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: legal and government | 1368 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: business and finance | 1366 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 5 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | Qwen3 14B | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | GPT-5.4 Nano | Qwen3 14B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 38.1% | Not measured | Only GPT-5.4 Nano measured |
| MedScribe (Vals AI) | 77.1% | Not measured | Only GPT-5.4 Nano measured |
| Vals Multimodal Index | 47.6% | Not measured | Only GPT-5.4 Nano measured |
| IFBench | 75.9% | 40.5% | GPT-5.4 Nano |
| Long context reasoning (AA-LCR) | 76.7% | 0.0% | GPT-5.4 Nano |
| DTBench | 80.3% | 64.0% | GPT-5.4 Nano |
| LMCA | 36.9% | 18.2% | GPT-5.4 Nano |
| Fiction.LiveBench | Not measured | 62.5% | Only Qwen3 14B measured |
| LMArena Text | 1372 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: instruction following | 1362 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: creative writing | 1315 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision | 1196 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: English | 1381 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: non-English | 1359 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Chinese | 1391 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: German | 1368 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Japanese | 1343 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Korean | 1321 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: French | 1395 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Spanish | 1371 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Russian | 1363 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: Polish | 1366 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: multi-turn | 1382 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: longer queries | 1365 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: writing and language | 1338 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Text: entertainment and media | 1325 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: English | 1202 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: Chinese | 1232 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: reading text | 1204 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: humor | 1161 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: recognizing things | 1141 | Not measured | Only GPT-5.4 Nano measured |
| LMArena Vision: creative writing | 1159 | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | Qwen3 14B | 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 | OpenAI GPT-5.4 Nano | Qwen3 14B |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | March 17, 2026 | April 28, 2025 |
| Context window | 400K | 41K |
| Input $/Mtok | $0.20 | $0.11 |
| Output $/Mtok | $1.25 | $0.23 |
| Coding index | 44.8 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | $0.14 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.4 Nano better than Qwen3 14B for coding?
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; Qwen3 14B has none, so the two cannot be ranked on coding. Pick Qwen3 14B for output tokens 5.4x cheaper ($0.23 vs $1.25 per million) and work measured by Kagi LLM Benchmark, where it leads.
Which is cheaper, GPT-5.4 Nano or Qwen3 14B?
GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens; Qwen3 14B costs $0.11 and $0.23. Cost per solved task is known for GPT-5.4 Nano only.
Which has the bigger context window, GPT-5.4 Nano or Qwen3 14B?
GPT-5.4 Nano, with 400K tokens against 41K.
How many benchmarks is the GPT-5.4 Nano vs Qwen3 14B comparison based on?
14 benchmarks have a result for both models as of October 22, 2026. GPT-5.4 Nano's coding index rests on 2 independent benchmarks and Qwen3 14B's on 0. Where only one model has a result, the page says so instead of naming a winner.