GPT-5.4 Nano vs Qwen3.6 Flash
GPT-5.4 Nano and Qwen3.6 Flash cost about the same per output token ($1.25 vs $1.125 per million). Updated October 22, 2026; 10 benchmarks have a result for both.
GPT-5.4 Nano or Qwen3.6 Flash: which to pick
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; Qwen3.6 Flash has none, so the two cannot be ranked on coding.
Pick Qwen3.6 Flash for output tokens 1.1x cheaper ($1.125 vs $1.25 per million) and a larger context window (1M against 400K tokens).
- Shared results
- 10
- GPT-5.4 Nano only
- 75
- Qwen3.6 Flash only
- 1
- 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
No call
Only GPT-5.4 Nano has a AA Intelligence Index result, 20.7.
Directional only
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
Qwen3.6 Flash
Qwen3.6 Flash takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.6 Flash
GPT-5.4 Nano $0.0008, Qwen3.6 Flash $0.0008 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, Qwen3.6 Flash not benchmarked.
- Widest category
- Coding, 22.6 points apart on average over 1 shared benchmark.
- Widest single gap
- Chess puzzles: GPT-5.4 Nano 45.0% against Qwen3.6 Flash 12.0%, 33.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.4 Nano $1.25 against Qwen3.6 Flash $1.125 per million output tokens, 1.1x apart.
- Context window
- GPT-5.4 Nano takes 400K tokens, Qwen3.6 Flash 1M.
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 | Qwen3.6 Flash | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 2 | ||
| Math | 2 | 0 | ||
| Knowledge | 0 | 1 | ||
| General | 2 | 0 | ||
| All shared boards | 7 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | GPT-5.4 Nano | Qwen3.6 Flash | 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 |
| SciCode | 47.2% | Not measured | Only GPT-5.4 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | Not measured | Only GPT-5.4 Nano measured |
| WeirdML | 49.2% | Not measured | Only GPT-5.4 Nano measured |
| ALE-Bench | 1004.5 | 326.4 | GPT-5.4 Nano |
| 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 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.4 Nano | Qwen3.6 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.7 | Not measured | Only GPT-5.4 Nano measured |
| Epoch Capabilities Index | 146.0 | 142.9 | GPT-5.4 Nano |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.4 Nano | Qwen3.6 Flash | 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% | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | GPT-5.4 Nano | Qwen3.6 Flash | 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% | Not measured | Only GPT-5.4 Nano measured |
| Humanity's Last Exam (Artificial Analysis run) | 28.3% | Not measured | Only GPT-5.4 Nano measured |
| GPQA Diamond (Epoch AI run) | 78.5% | 83.3% | Qwen3.6 Flash |
| 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 |
| SimpleBench | Not measured | 35.2% | Only Qwen3.6 Flash measured |
| Chess puzzles | 45.0% | 12.0% | GPT-5.4 Nano |
| Mystery game puzzles | 9.0% | 18.0% | Qwen3.6 Flash |
| 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% | Not measured | Only GPT-5.4 Nano measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 Nano | Qwen3.6 Flash | Leader |
|---|---|---|---|
| AIME | 88.8% | Not measured | Only GPT-5.4 Nano measured |
| OTIS Mock AIME | 87.8% | 84.4% | GPT-5.4 Nano |
| FrontierMath, tiers 1 to 3 | 44.9% | 22.5% | GPT-5.4 Nano |
| 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 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.4 Nano | Qwen3.6 Flash | 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 |
| SimpleQA Verified | 11.7% | 15.9% | Qwen3.6 Flash |
| 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 6 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | Qwen3.6 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.4 Nano | Qwen3.6 Flash | 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% | Not measured | Only GPT-5.4 Nano measured |
| Long context reasoning (AA-LCR) | 76.7% | Not measured | Only GPT-5.4 Nano measured |
| DTBench | 80.3% | 77.1% | GPT-5.4 Nano |
| LMCA | 36.9% | 31.0% | GPT-5.4 Nano |
| 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 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.4 Nano | Qwen3.6 Flash | 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
Qwen3.6 Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.6 Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.6 Flash 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 | Qwen3.6 Flash |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | March 17, 2026 | April 27, 2026 |
| Context window | 400K | 1M |
| Input $/Mtok | $0.20 | $0.1875 |
| Output $/Mtok | $1.25 | $1.125 |
| 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 Qwen3.6 Flash for coding?
Only GPT-5.4 Nano has a coding score, 44.8 on the Vibe Coding Index; Qwen3.6 Flash has none, so the two cannot be ranked on coding. Pick Qwen3.6 Flash for output tokens 1.1x cheaper ($1.125 vs $1.25 per million) and a larger context window (1M against 400K tokens).
Which is cheaper, GPT-5.4 Nano or Qwen3.6 Flash?
GPT-5.4 Nano costs $0.20 per million input tokens and $1.25 per million output tokens; Qwen3.6 Flash costs $0.1875 and $1.125. Cost per solved task is known for GPT-5.4 Nano only.
Which has the bigger context window, GPT-5.4 Nano or Qwen3.6 Flash?
Qwen3.6 Flash, with 1M tokens against 400K.
How many benchmarks is the GPT-5.4 Nano vs Qwen3.6 Flash comparison based on?
10 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 Qwen3.6 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.