GPT-5.1-Codex vs Qwen3.5 397B A17B
GPT-5.1-Codex leads Qwen3.5 397B A17B on the Artificial Analysis Intelligence Index, 23.7 to 21.4, and Qwen3.5 397B A17B costs 4.3x less per output token ($2.34 vs $10.00 per million). Updated October 22, 2026; 15 benchmarks have a result for both.
GPT-5.1-Codex or Qwen3.5 397B A17B: which to pick
Only GPT-5.1-Codex has a coding score, 15.3 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding.
Pick Qwen3.5 397B A17B for output tokens 4.3x cheaper ($2.34 vs $10.00 per million) and work measured by LMArena WebDev or Terminal-Bench Hard (Artificial Analysis run), where it leads.
- Shared results
- 15
- GPT-5.1-Codex only
- 11
- Qwen3.5 397B A17B only
- 50
- 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-5.1-Codex has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.1-Codex
GPT-5.1-Codex leads, 23.7 against 21.4.
Same board, both measured
Web design
Design Arena: websites
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 1190 against 1161.
Same board, both measured
Long documents
Listed context window
GPT-5.1-Codex
GPT-5.1-Codex takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5 397B A17B
GPT-5.1-Codex $0.0063, Qwen3.5 397B A17B $0.0016 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.1-Codex has the number, $0.892.
Directional only
At a glance
- Coding index
- GPT-5.1-Codex 15.3 from 2 benchmarks, Qwen3.5 397B A17B not benchmarked.
- Widest category
- Agentic work, 12.6 points apart on average over 1 shared benchmark.
- Widest single gap
- ALE-Bench: GPT-5.1-Codex 1244.9 against Qwen3.5 397B A17B 621.9, 20.8 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex $10.00 against Qwen3.5 397B A17B $2.34 per million output tokens, 4.3x apart.
- Context window
- GPT-5.1-Codex takes 400K tokens, Qwen3.5 397B A17B 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 | GPT-5.1-Codex | Bars | Qwen3.5 397B A17B | Ties |
|---|---|---|---|---|
| Coding | 1 | 3 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Web design | 2 | 3 | ||
| General | 0 | 2 | ||
| All shared boards | 4 | 11 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index13
| Benchmark | GPT-5.1-Codex | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| SWE-bench Verified | 66.0% | Not measured | Only GPT-5.1-Codex measured |
| LMArena WebDev | 1337 | 1400 | Qwen3.5 397B A17B |
| LiveCodeBench (Vals AI) | 85.5% | Not measured | Only GPT-5.1-Codex measured |
| Vibe Code Bench (Vals AI) | 13.1% | Not measured | Only GPT-5.1-Codex measured |
| LiveCodeBench (Artificial Analysis run) | 84.9% | Not measured | Only GPT-5.1-Codex measured |
| SciCode | Not measured | 44.8% | Only Qwen3.5 397B A17B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 34.8% | 40.9% | Qwen3.5 397B A17B |
| Terminal-Bench | 57.8% | Not measured | Only GPT-5.1-Codex measured |
| ALE-Bench | 1244.9 | 621.9 | GPT-5.1-Codex |
| LMArena Text: coding | Not measured | 1464 | Only Qwen3.5 397B A17B measured |
| LMArena Text: software and IT | Not measured | 1463 | Only Qwen3.5 397B A17B measured |
| LMArena WebDev: React | Not measured | 1388 | Only Qwen3.5 397B A17B measured |
| LMArena WebDev: HTML | 1346 | 1410 | Qwen3.5 397B A17B |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.7 | 21.4 | GPT-5.1-Codex |
| Epoch Capabilities Index | Not measured | 146.8 | Only Qwen3.5 397B A17B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.1-Codex | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1018 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: agents building full-stack apps | 1086 | Not measured | Only GPT-5.1-Codex measured |
| Design Arena: agents building mobile apps | 1191 | Not measured | Only GPT-5.1-Codex measured |
| τ²-Bench Telecom | 83.0% | 95.6% | Qwen3.5 397B A17B |
| APEX-Agents | Not measured | 24.9% | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5.1-Codex | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 86.0% | 89.3% | Qwen3.5 397B A17B |
| Humanity's Last Exam (Artificial Analysis run) | 25.7% | 29.0% | Qwen3.5 397B A17B |
| GPQA Diamond (Epoch AI run) | Not measured | 86.4% | Only Qwen3.5 397B A17B measured |
| Mystery game puzzles | Not measured | 18.0% | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts | Not measured | 1448 | Only Qwen3.5 397B A17B measured |
| LMArena Text: expert | Not measured | 1462 | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts in English | Not measured | 1450 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: diagrams | Not measured | 1277 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: homework | Not measured | 1292 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.1-Codex | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Math Index | 95.7 | Not measured | Only GPT-5.1-Codex measured |
| AIME 2025 (Artificial Analysis run) | 95.7% | Not measured | Only GPT-5.1-Codex measured |
| OTIS Mock AIME | Not measured | 88.9% | Only Qwen3.5 397B A17B measured |
| FrontierMath, tiers 1 to 3 | Not measured | 31.2% | Only Qwen3.5 397B A17B measured |
| LMArena Text: math | Not measured | 1453 | Only Qwen3.5 397B A17B measured |
| LMArena Text: mathematical work | Not measured | 1454 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | GPT-5.1-Codex | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 86.0% | Not measured | Only GPT-5.1-Codex measured |
| LMArena Text: science | Not measured | 1457 | Only Qwen3.5 397B A17B measured |
| LMArena Text: medicine and healthcare | Not measured | 1455 | Only Qwen3.5 397B A17B measured |
| LMArena Text: legal and government | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: business and finance | Not measured | 1435 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | GPT-5.1-Codex | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Design Arena: websites | 1161 | 1190 | Qwen3.5 397B A17B |
| Design Arena: UI components | 1234 | 1160 | GPT-5.1-Codex |
| Design Arena: game dev | 1137 | 1140 | Qwen3.5 397B A17B |
| Design Arena: data viz | 1213 | 1175 | GPT-5.1-Codex |
| Design Arena: 3D | Not measured | 1160 | Only Qwen3.5 397B A17B measured |
| Design Arena: all code categories | 1152 | 1179 | Qwen3.5 397B A17B |
| Design Arena: SVG | Not measured | 1139 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5.1-Codex | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| IFBench | 70.0% | 78.8% | Qwen3.5 397B A17B |
| Long context reasoning (AA-LCR) | 69.3% | 77.3% | Qwen3.5 397B A17B |
| DTBench | Not measured | 87.5% | Only Qwen3.5 397B A17B measured |
| LMCA | Not measured | 37.9% | Only Qwen3.5 397B A17B measured |
| LMArena Text | Not measured | 1437 | Only Qwen3.5 397B A17B measured |
| LMArena Text: instruction following | Not measured | 1424 | Only Qwen3.5 397B A17B measured |
| LMArena Text: creative writing | Not measured | 1402 | Only Qwen3.5 397B A17B measured |
| LMArena Vision | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Text: English | Not measured | 1443 | Only Qwen3.5 397B A17B measured |
| LMArena Text: non-English | Not measured | 1430 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Chinese | Not measured | 1498 | Only Qwen3.5 397B A17B measured |
| LMArena Text: German | Not measured | 1445 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Japanese | Not measured | 1429 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Korean | Not measured | 1384 | Only Qwen3.5 397B A17B measured |
| LMArena Text: French | Not measured | 1462 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Spanish | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Russian | Not measured | 1430 | Only Qwen3.5 397B A17B measured |
| LMArena Text: Polish | Not measured | 1447 | Only Qwen3.5 397B A17B measured |
| LMArena Text: multi-turn | Not measured | 1446 | Only Qwen3.5 397B A17B measured |
| LMArena Text: longer queries | Not measured | 1441 | Only Qwen3.5 397B A17B measured |
| LMArena Text: writing and language | Not measured | 1415 | Only Qwen3.5 397B A17B measured |
| LMArena Text: entertainment and media | Not measured | 1399 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: English | Not measured | 1268 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: Chinese | Not measured | 1314 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: reading text | Not measured | 1271 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: humor | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: captioning | Not measured | 1230 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: recognizing things | Not measured | 1265 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: creative writing | Not measured | 1260 | Only Qwen3.5 397B A17B 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-5.1-Codex | Qwen3.5 397B A17B | 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
Qwen3.5 397B A17B costs less
Repository review
50K input + 3K output tokens
Qwen3.5 397B A17B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 397B A17B 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-5.1-Codex | Qwen3.5 397B A17B |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | November 13, 2025 | February 16, 2026 |
| Context window | 400K | 262K |
| Input $/Mtok | $1.25 | $0.39 |
| Output $/Mtok | $10.00 | $2.34 |
| Coding index | 15.3 | Not benchmarked |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.892 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex better than Qwen3.5 397B A17B for coding?
Only GPT-5.1-Codex has a coding score, 15.3 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding. Pick Qwen3.5 397B A17B for output tokens 4.3x cheaper ($2.34 vs $10.00 per million) and work measured by LMArena WebDev or Terminal-Bench Hard (Artificial Analysis run), where it leads.
Which is cheaper, GPT-5.1-Codex or Qwen3.5 397B A17B?
GPT-5.1-Codex costs $1.25 per million input tokens and $10.00 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for GPT-5.1-Codex only.
Which has the bigger context window, GPT-5.1-Codex or Qwen3.5 397B A17B?
GPT-5.1-Codex, with 400K tokens against 262K.
How many benchmarks is the GPT-5.1-Codex vs Qwen3.5 397B A17B comparison based on?
15 benchmarks have a result for both models as of October 22, 2026. GPT-5.1-Codex's coding index rests on 2 independent benchmarks and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.