GPT-5 Nano vs Qwen3.8 Flash
Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
GPT-5 Nano scores 34.8 and Qwen3.8 Flash 87.4 on the Vibe Coding Index, but no coding benchmark measured both, so the gap is directional, not a ranking.
Pick GPT-5 Nano when output tokens cost 1.2x less; pick Qwen3.8 Flash when the context window is larger, 1M against 400K tokens.
- Shared results
- 0
- GPT-5 Nano only
- 85
- Qwen3.8 Flash only
- 7
- Like-for-like categories
- 0 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
No call
34.8 against 87.4, from different benchmarks with none in common.
Directional only
Intelligence
AA Intelligence Index
No call
Only GPT-5 Nano has a AA Intelligence Index result, 13.0.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5 Nano has a GPQA Diamond result, 63.4%.
Directional only
Math
AIME
No call
Only GPT-5 Nano has a AIME result, 81.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5 Nano has a MMLU Pro result, 76.1%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5 Nano has a Design Arena: websites result, 1101.
Directional only
Long documents
Listed context window
Qwen3.8 Flash
Qwen3.8 Flash takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5 Nano
GPT-5 Nano $0.0003, Qwen3.8 Flash $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5 Nano has the number, $0.109.
Directional only
At a glance
- Coding index
- GPT-5 Nano 34.8 from 1 benchmark, Qwen3.8 Flash 87.4 from 1 benchmark.
- Widest category
- No category has a result for both models.
- Widest single gap
- No benchmark has a result for both models.
- Output price
- GPT-5 Nano $0.40 against Qwen3.8 Flash $0.47 per million output tokens, 1.2x apart.
- Context window
- GPT-5 Nano takes 400K tokens, Qwen3.8 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.
CodingDirectional onlyFour of these boards feed the Vibe Coding Index9 boards, none shared
| Benchmark | GPT-5 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| SWE-bench Verified | 34.8% | Not measured | Only GPT-5 Nano measured |
| LiveBench coding | Not measured | 87.4% | Only Qwen3.8 Flash measured |
| LiveCodeBench (Vals AI) | 70.2% | Not measured | Only GPT-5 Nano measured |
| LiveCodeBench (Artificial Analysis run) | 78.9% | Not measured | Only GPT-5 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 17.4% | Not measured | Only GPT-5 Nano measured |
| Terminal-Bench | 21.8% | Not measured | Only GPT-5 Nano measured |
| WeirdML | 38.1% | Not measured | Only GPT-5 Nano measured |
| LMArena Text: coding | 1351 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: software and IT | 1345 | Not measured | Only GPT-5 Nano measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.0 | Not measured | Only GPT-5 Nano measured |
| Epoch Capabilities Index | 139.2 | Not measured | Only GPT-5 Nano measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-5 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 74.6% | Only Qwen3.8 Flash measured |
| LiveBench browser | Not measured | 48.0% | Only Qwen3.8 Flash measured |
| LiveBench long agentic | Not measured | 37.1% | Only Qwen3.8 Flash measured |
| τ²-Bench Telecom | 36.5% | Not measured | Only GPT-5 Nano measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | GPT-5 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | 63.4% | Not measured | Only GPT-5 Nano measured |
| LiveBench reasoning | Not measured | 87.4% | Only Qwen3.8 Flash measured |
| MMMU Pro (Vals AI) | 70.9% | Not measured | Only GPT-5 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 67.6% | Not measured | Only GPT-5 Nano measured |
| Humanity's Last Exam (Artificial Analysis run) | 9.5% | Not measured | Only GPT-5 Nano measured |
| GPQA Diamond (Epoch AI run) | 69.4% | Not measured | Only GPT-5 Nano measured |
| ARC-AGI | 20.7% | Not measured | Only GPT-5 Nano measured |
| ARC-AGI-2 | 2.6% | Not measured | Only GPT-5 Nano measured |
| Chess puzzles | 22.0% | Not measured | Only GPT-5 Nano measured |
| Mystery game puzzles | 9.0% | Not measured | Only GPT-5 Nano measured |
| VPCT | 37.2% | Not measured | Only GPT-5 Nano measured |
| LMArena Text: hard prompts | 1328 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: expert | 1321 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: hard prompts in English | 1338 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: diagrams | 1141 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: homework | 1157 | Not measured | Only GPT-5 Nano measured |
| Neither model has a result on the other 5 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GPT-5 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| AIME | 81.2% | Not measured | Only GPT-5 Nano measured |
| MATH 500 (Vals AI) | 93.8% | Not measured | Only GPT-5 Nano measured |
| MGSM (Vals AI) | 89.3% | Not measured | Only GPT-5 Nano measured |
| AA Math Index | 83.7 | Not measured | Only GPT-5 Nano measured |
| AIME 2025 (Artificial Analysis run) | 83.7% | Not measured | Only GPT-5 Nano measured |
| OTIS Mock AIME | 81.1% | Not measured | Only GPT-5 Nano measured |
| FrontierMath, tiers 1 to 3 | 20.0% | Not measured | Only GPT-5 Nano measured |
| FrontierMath, tier 4 | 2.4% | Not measured | Only GPT-5 Nano measured |
| ProofBench | 12.0% | Not measured | Only GPT-5 Nano measured |
| MATH level 5 | 95.2% | Not measured | Only GPT-5 Nano measured |
| LMArena Text: math | 1317 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: mathematical work | 1326 | Not measured | Only GPT-5 Nano measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | GPT-5 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| MMLU Pro | 76.1% | Not measured | Only GPT-5 Nano measured |
| LegalBench (Vals AI) | 50.1% | Not measured | Only GPT-5 Nano measured |
| CaseLaw (Vals AI) | 52.6% | Not measured | Only GPT-5 Nano measured |
| TaxEval (Vals AI) | 67.4% | Not measured | Only GPT-5 Nano measured |
| MortgageTax (Vals AI) | 53.6% | Not measured | Only GPT-5 Nano measured |
| MedQA (Vals AI) | 93.3% | Not measured | Only GPT-5 Nano measured |
| MedCode (Vals AI) | 30.4% | Not measured | Only GPT-5 Nano measured |
| MMLU Pro (Artificial Analysis run) | 78.0% | Not measured | Only GPT-5 Nano measured |
| SimpleQA Verified | 11.7% | Not measured | Only GPT-5 Nano measured |
| LMArena Text: science | 1318 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: medicine and healthcare | 1335 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: legal and government | 1298 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: business and finance | 1311 | Not measured | Only GPT-5 Nano measured |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-5 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1101 | Not measured | Only GPT-5 Nano measured |
| Design Arena: UI components | 1066 | Not measured | Only GPT-5 Nano measured |
| Design Arena: game dev | 1045 | Not measured | Only GPT-5 Nano measured |
| Design Arena: data viz | 1056 | Not measured | Only GPT-5 Nano measured |
| Design Arena: 3D | 966 | Not measured | Only GPT-5 Nano measured |
| Design Arena: all code categories | 1084 | Not measured | Only GPT-5 Nano measured |
| LiveBench design | Not measured | 72.8% | Only Qwen3.8 Flash measured |
| Neither model has a result on the other 2 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index29 boards, none shared
| Benchmark | GPT-5 Nano | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 74.2% | Only Qwen3.8 Flash measured |
| SAGE (Vals AI) | 30.4% | Not measured | Only GPT-5 Nano measured |
| MedScribe (Vals AI) | 72.9% | Not measured | Only GPT-5 Nano measured |
| IFBench | 67.6% | Not measured | Only GPT-5 Nano measured |
| Long context reasoning (AA-LCR) | 45.0% | Not measured | Only GPT-5 Nano measured |
| DTBench | 62.7% | Not measured | Only GPT-5 Nano measured |
| LMCA | 7.9% | Not measured | Only GPT-5 Nano measured |
| Fiction.LiveBench | 44.4% | Not measured | Only GPT-5 Nano measured |
| LMArena Text | 1320 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: instruction following | 1306 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: creative writing | 1249 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision | 1159 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: English | 1321 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: non-English | 1313 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Chinese | 1356 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: German | 1327 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Japanese | 1227 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Korean | 1269 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Spanish | 1360 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Russian | 1296 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: Polish | 1314 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: multi-turn | 1311 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: longer queries | 1312 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: writing and language | 1283 | Not measured | Only GPT-5 Nano measured |
| LMArena Text: entertainment and media | 1268 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: English | 1170 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: Chinese | 1176 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: reading text | 1152 | Not measured | Only GPT-5 Nano measured |
| LMArena Vision: humor | 1110 | Not measured | Only GPT-5 Nano measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5 Nano | Qwen3.8 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
GPT-5 Nano costs less
Repository review
50K input + 3K output tokens
GPT-5 Nano costs less
Agent loop
200K input + 10K output tokens
GPT-5 Nano 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 Nano | Qwen3.8 Flash |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | August 7, 2025 | August 26, 2026 |
| Context window | 400K | 1M |
| Input $/Mtok | $0.05 | $0.15 |
| Output $/Mtok | $0.40 | $0.47 |
| Coding index | 34.8 | 87.4 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $0.109 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 Nano better than Qwen3.8 Flash for coding?
GPT-5 Nano scores 34.8 and Qwen3.8 Flash 87.4 on the Vibe Coding Index, but no coding benchmark measured both, so the gap is directional, not a ranking. Pick GPT-5 Nano when output tokens cost 1.2x less; pick Qwen3.8 Flash when the context window is larger, 1M against 400K tokens.
Which is cheaper, GPT-5 Nano or Qwen3.8 Flash?
GPT-5 Nano costs $0.05 per million input tokens and $0.40 per million output tokens; Qwen3.8 Flash costs $0.15 and $0.47. Cost per solved task is known for GPT-5 Nano only.
Which has the bigger context window, GPT-5 Nano or Qwen3.8 Flash?
Qwen3.8 Flash, with 1M tokens against 400K.
How many benchmarks is the GPT-5 Nano vs Qwen3.8 Flash comparison based on?
0 benchmarks have a result for both models as of October 21, 2026. GPT-5 Nano's coding index rests on 1 independent benchmark and Qwen3.8 Flash's on 1. Where only one model has a result, the page says so instead of naming a winner.