GPT-4o (2024-11-20) vs Qwen3.6 27B
Qwen3.6 27B leads GPT-4o (2024-11-20) on the Artificial Analysis Intelligence Index, 21.4 to 8.4, and Qwen3.6 27B costs 3.7x less per output token ($2.70 vs $10.00 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
GPT-4o (2024-11-20) or Qwen3.6 27B: which to pick
Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; GPT-4o (2024-11-20) has none, so the two cannot be ranked on coding.
Pick GPT-4o (2024-11-20) for work measured by CaseLaw (Vals AI) or TaxEval (Vals AI), where it leads.
- Shared results
- 7
- GPT-4o (2024-11-20) only
- 17
- Qwen3.6 27B only
- 18
- Like-for-like categories
- 4 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 Qwen3.6 27B has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.6 27B
Qwen3.6 27B leads, 21.4 against 8.4.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.6 27B has a AA Agentic Index result, 18.5.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-4o (2024-11-20) has a GPQA Diamond result, 53.8%.
Directional only
Math
AIME
No call
Only GPT-4o (2024-11-20) has a AIME result, 11.9%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o (2024-11-20) has a MMLU Pro result, 72.6%.
Directional only
Long documents
Listed context window
Qwen3.6 27B
Qwen3.6 27B takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.6 27B
GPT-4o (2024-11-20) $0.0075, Qwen3.6 27B $0.0018 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.6 27B has the number, $1.30.
Directional only
At a glance
- Coding index
- GPT-4o (2024-11-20) not benchmarked, Qwen3.6 27B 36.8 from 2 benchmarks.
- Widest category
- Math, 84.9 points apart on average over 1 shared benchmark.
- Widest single gap
- OTIS Mock AIME: GPT-4o (2024-11-20) 6.3% against Qwen3.6 27B 91.1%, 84.9 points apart on a 0 to 100 scale.
- Output price
- GPT-4o (2024-11-20) $10.00 against Qwen3.6 27B $2.70 per million output tokens, 3.7x apart.
- Context window
- GPT-4o (2024-11-20) takes 128K tokens, Qwen3.6 27B 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-4o (2024-11-20) | Bars | Qwen3.6 27B | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| Math | 0 | 1 | ||
| Knowledge | 2 | 2 | ||
| All shared boards | 2 | 5 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index10 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | Qwen3.6 27B | Leader |
|---|---|---|---|
| Aider polyglot | 18.2% | Not measured | Only GPT-4o (2024-11-20) measured |
| AA Coding Index | Not measured | 53.7 | Only Qwen3.6 27B measured |
| LiveCodeBench (Vals AI) | 43.4% | Not measured | Only GPT-4o (2024-11-20) measured |
| SWE-bench Verified (Vals AI) | Not measured | 70.0% | Only Qwen3.6 27B measured |
| Vibe Code Bench (Vals AI) | Not measured | 11.9% | Only Qwen3.6 27B measured |
| SciCode | Not measured | 42.8% | Only Qwen3.6 27B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 34.8% | Only Qwen3.6 27B measured |
| GSO-Bench | 0.0% | Not measured | Only GPT-4o (2024-11-20) measured |
| WeirdML | 25.1% | Not measured | Only GPT-4o (2024-11-20) measured |
| Cybench | 12.5% | Not measured | Only GPT-4o (2024-11-20) 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 | GPT-4o (2024-11-20) | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 8.4 | 21.4 | Qwen3.6 27B |
| Epoch Capabilities Index | Not measured | 146.2 | Only Qwen3.6 27B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 18.5 | Only Qwen3.6 27B measured |
| τ²-Bench Telecom | Not measured | 94.2% | Only Qwen3.6 27B measured |
| TheAgentCompany | 8.6% | Not measured | Only GPT-4o (2024-11-20) measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o (2024-11-20) | Qwen3.6 27B | Leader |
|---|---|---|---|
| GPQA Diamond | 53.8% | Not measured | Only GPT-4o (2024-11-20) measured |
| MMMU Pro (Vals AI) | 62.2% | Not measured | Only GPT-4o (2024-11-20) measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 84.2% | Only Qwen3.6 27B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 23.1% | Only Qwen3.6 27B measured |
| GPQA Diamond (Epoch AI run) | 47.9% | 85.9% | Qwen3.6 27B |
| Mystery game puzzles | Not measured | 7.0% | Only Qwen3.6 27B measured |
| VPCT | 40.0% | Not measured | Only GPT-4o (2024-11-20) measured |
| Neither model has a result on the other 16 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o (2024-11-20) | Qwen3.6 27B | Leader |
|---|---|---|---|
| AIME | 11.9% | Not measured | Only GPT-4o (2024-11-20) measured |
| MATH 500 (Vals AI) | 74.0% | Not measured | Only GPT-4o (2024-11-20) measured |
| MGSM (Vals AI) | 90.4% | Not measured | Only GPT-4o (2024-11-20) measured |
| OTIS Mock AIME | 6.3% | 91.1% | Qwen3.6 27B |
| FrontierMath, tiers 1 to 3 | Not measured | 35.1% | Only Qwen3.6 27B measured |
| MATH level 5 | 49.8% | Not measured | Only GPT-4o (2024-11-20) measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | GPT-4o (2024-11-20) | Qwen3.6 27B | Leader |
|---|---|---|---|
| MMLU Pro | 72.6% | Not measured | Only GPT-4o (2024-11-20) measured |
| LegalBench (Vals AI) | 82.2% | Not measured | Only GPT-4o (2024-11-20) measured |
| CaseLaw (Vals AI) | 59.7% | 53.2% | GPT-4o (2024-11-20) |
| CorpFin (Vals AI) | 45.9% | 62.3% | Qwen3.6 27B |
| TaxEval (Vals AI) | 74.5% | 71.3% | GPT-4o (2024-11-20) |
| MortgageTax (Vals AI) | 57.4% | 68.3% | Qwen3.6 27B |
| GeoBench | 71.0% | Not measured | Only GPT-4o (2024-11-20) measured |
| Neither model has a result on the other 13 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | Qwen3.6 27B | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | Qwen3.6 27B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 45.6% | Only Qwen3.6 27B measured |
| IFBench | Not measured | 67.6% | Only Qwen3.6 27B measured |
| Long context reasoning (AA-LCR) | Not measured | 77.3% | Only Qwen3.6 27B measured |
| DTBench | Not measured | 78.1% | Only Qwen3.6 27B measured |
| LMCA | Not measured | 34.5% | Only Qwen3.6 27B measured |
| Creative writing (Lech Mazur) | 81.8% | Not measured | Only GPT-4o (2024-11-20) measured |
| EQ-Bench 4 | Not measured | 1026 | Only Qwen3.6 27B 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 | GPT-4o (2024-11-20) | Qwen3.6 27B | 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 27B costs less
Repository review
50K input + 3K output tokens
Qwen3.6 27B costs less
Agent loop
200K input + 10K output tokens
Qwen3.6 27B 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-4o (2024-11-20) | Qwen3.6 27B |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | November 20, 2024 | April 27, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $2.50 | $0.45 |
| Output $/Mtok | $10.00 | $2.70 |
| Coding index | Not benchmarked | 36.8 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | $1.30 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o (2024-11-20) better than Qwen3.6 27B for coding?
Only Qwen3.6 27B has a coding score, 36.8 on the Vibe Coding Index; GPT-4o (2024-11-20) has none, so the two cannot be ranked on coding. Pick GPT-4o (2024-11-20) for work measured by CaseLaw (Vals AI) or TaxEval (Vals AI), where it leads.
Which is cheaper, GPT-4o (2024-11-20) or Qwen3.6 27B?
GPT-4o (2024-11-20) costs $2.50 per million input tokens and $10.00 per million output tokens; Qwen3.6 27B costs $0.45 and $2.70. Cost per solved task is known for Qwen3.6 27B only.
Which has the bigger context window, GPT-4o (2024-11-20) or Qwen3.6 27B?
Qwen3.6 27B, with 262K tokens against 128K.
How many benchmarks is the GPT-4o (2024-11-20) vs Qwen3.6 27B comparison based on?
7 benchmarks have a result for both models as of October 22, 2026. GPT-4o (2024-11-20)'s coding index rests on 0 independent benchmarks and Qwen3.6 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.