GPT-4o (2024-11-20) vs Qwen2.5 72B Instruct
GPT-4o (2024-11-20) leads Qwen2.5 72B Instruct on the Artificial Analysis Intelligence Index, 8.4 to 7.7, and Qwen2.5 72B Instruct costs 25.0x less per output token ($0.40 vs $10.00 per million). Updated October 23, 2026; 6 benchmarks have a result for both.
GPT-4o (2024-11-20) or Qwen2.5 72B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o (2024-11-20) for a larger context window (128K against 33K tokens) and work measured by GPQA Diamond (Epoch AI run) or OTIS Mock AIME, where it leads.
- Shared results
- 6
- GPT-4o (2024-11-20) only
- 18
- Qwen2.5 72B Instruct only
- 47
- Like-for-like categories
- 5 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
GPT-4o (2024-11-20)
GPT-4o (2024-11-20) leads, 8.4 against 7.7.
Same board, both measured
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
GPT-4o (2024-11-20)
GPT-4o (2024-11-20) takes 128K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 72B Instruct
GPT-4o (2024-11-20) $0.0075, Qwen2.5 72B Instruct $0.0006 per turn.
List prices
At a glance
- Coding index
- GPT-4o (2024-11-20) not benchmarked, Qwen2.5 72B Instruct not benchmarked.
- Widest category
- Coding, 9.2 points apart on average over 1 shared benchmark.
- Widest single gap
- MATH level 5: GPT-4o (2024-11-20) 49.8% against Qwen2.5 72B Instruct 63.2%, 13.4 points apart on a 0 to 100 scale.
- Output price
- GPT-4o (2024-11-20) $10.00 against Qwen2.5 72B Instruct $0.40 per million output tokens, 25.0x apart.
- Context window
- GPT-4o (2024-11-20) takes 128K tokens, Qwen2.5 72B Instruct 33K.
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 | Qwen2.5 72B Instruct | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 0 | 1 | ||
| Math | 0 | 2 | ||
| All shared boards | 3 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | GPT-4o (2024-11-20) | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | 18.2% | Not measured | Only GPT-4o (2024-11-20) measured |
| LiveCodeBench (Vals AI) | 43.4% | Not measured | Only GPT-4o (2024-11-20) measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 27.6% | Only Qwen2.5 72B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 4.5% | Only Qwen2.5 72B Instruct measured |
| GSO-Bench | 0.0% | Not measured | Only GPT-4o (2024-11-20) measured |
| WeirdML | 25.1% | 16.0% | GPT-4o (2024-11-20) |
| Cybench | 12.5% | Not measured | Only GPT-4o (2024-11-20) measured |
| LMArena Text: coding | Not measured | 1292 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: software and IT | Not measured | 1292 | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-4o (2024-11-20) | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 8.4 | 7.7 | GPT-4o (2024-11-20) |
| Epoch Capabilities Index | Not measured | 129.0 | Only Qwen2.5 72B Instruct measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-4o (2024-11-20) | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 34.5% | Only Qwen2.5 72B Instruct measured |
| METR time horizons | Not measured | 35.8% | Only Qwen2.5 72B Instruct measured |
| BALROG | Not measured | 16.2% | Only Qwen2.5 72B Instruct measured |
| TheAgentCompany | 8.6% | 5.7% | GPT-4o (2024-11-20) |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4o (2024-11-20) | Qwen2.5 72B Instruct | 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 | 49.1% | Only Qwen2.5 72B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 3.6% | Only Qwen2.5 72B Instruct measured |
| GPQA Diamond (Epoch AI run) | 47.9% | 49.1% | Qwen2.5 72B Instruct |
| VPCT | 40.0% | Not measured | Only GPT-4o (2024-11-20) measured |
| BIG-Bench Hard | Not measured | 79.8% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts | Not measured | 1270 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: expert | Not measured | 1245 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts in English | Not measured | 1279 | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-4o (2024-11-20) | Qwen2.5 72B Instruct | 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 |
| AA Math Index | Not measured | 14.0 | Only Qwen2.5 72B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 14.0% | Only Qwen2.5 72B Instruct measured |
| OTIS Mock AIME | 6.3% | 8.1% | Qwen2.5 72B Instruct |
| MATH level 5 | 49.8% | 63.2% | Qwen2.5 72B Instruct |
| LMArena Text: math | Not measured | 1283 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: mathematical work | Not measured | 1290 | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | Qwen2.5 72B Instruct | 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% | Not measured | Only GPT-4o (2024-11-20) measured |
| CorpFin (Vals AI) | 45.9% | Not measured | Only GPT-4o (2024-11-20) measured |
| TaxEval (Vals AI) | 74.5% | Not measured | Only GPT-4o (2024-11-20) measured |
| MortgageTax (Vals AI) | 57.4% | Not measured | Only GPT-4o (2024-11-20) measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 72.0% | Only Qwen2.5 72B Instruct measured |
| MMLU | Not measured | 85.3% | Only Qwen2.5 72B Instruct measured |
| GeoBench | 71.0% | Not measured | Only GPT-4o (2024-11-20) measured |
| AI2 Reasoning Challenge | Not measured | 94.5% | Only Qwen2.5 72B Instruct measured |
| LMArena Text: science | Not measured | 1275 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: medicine and healthcare | Not measured | 1258 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: legal and government | Not measured | 1288 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: business and finance | Not measured | 1253 | Only Qwen2.5 72B Instruct 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-4o (2024-11-20) | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index23 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | Qwen2.5 72B Instruct | Leader |
|---|---|---|---|
| IFBench | Not measured | 36.9% | Only Qwen2.5 72B Instruct measured |
| DTBench | Not measured | 62.9% | Only Qwen2.5 72B Instruct measured |
| LMCA | Not measured | 13.4% | Only Qwen2.5 72B Instruct measured |
| Creative writing (Lech Mazur) | 81.8% | Not measured | Only GPT-4o (2024-11-20) measured |
| HellaSwag | Not measured | 84.8% | Only Qwen2.5 72B Instruct measured |
| WinoGrande | Not measured | 82.3% | Only Qwen2.5 72B Instruct measured |
| PIQA | Not measured | 82.6% | Only Qwen2.5 72B Instruct measured |
| LMArena Text | Not measured | 1269 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: instruction following | Not measured | 1254 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: creative writing | Not measured | 1221 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: English | Not measured | 1283 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: non-English | Not measured | 1252 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Chinese | Not measured | 1273 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: German | Not measured | 1234 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Japanese | Not measured | 1180 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Korean | Not measured | 1188 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: French | Not measured | 1280 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Spanish | Not measured | 1256 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Russian | Not measured | 1264 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: multi-turn | Not measured | 1272 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: longer queries | Not measured | 1281 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: writing and language | Not measured | 1247 | Only Qwen2.5 72B Instruct measured |
| LMArena Text: entertainment and media | Not measured | 1211 | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4o (2024-11-20) | Qwen2.5 72B Instruct | 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
Qwen2.5 72B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 72B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 72B Instruct 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) | Qwen2.5 72B Instruct |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | November 20, 2024 | September 19, 2024 |
| Context window | 128K | 33K |
| Input $/Mtok | $2.50 | $0.36 |
| Output $/Mtok | $10.00 | $0.40 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o (2024-11-20) better than Qwen2.5 72B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o (2024-11-20) for a larger context window (128K against 33K tokens) and work measured by GPQA Diamond (Epoch AI run) or OTIS Mock AIME, where it leads.
Which is cheaper, GPT-4o (2024-11-20) or Qwen2.5 72B Instruct?
GPT-4o (2024-11-20) costs $2.50 per million input tokens and $10.00 per million output tokens; Qwen2.5 72B Instruct costs $0.36 and $0.40. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o (2024-11-20) or Qwen2.5 72B Instruct?
GPT-4o (2024-11-20), with 128K tokens against 33K.
How many benchmarks is the GPT-4o (2024-11-20) vs Qwen2.5 72B Instruct comparison based on?
6 benchmarks have a result for both models as of October 23, 2026. GPT-4o (2024-11-20)'s coding index rests on 0 independent benchmarks and Qwen2.5 72B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.