GPT-4o vs GPT-4o mini vs Qwen2.5 72B Instruct
GPT-4o mini comes out ahead, 56 to 43 and 40 on our weighted score, and it is the cheaper option too.
OpenAI
GPT-4o
43/100- ECI129.0
- Price$2.50 / $10.00
- Context128K
- Our pick
OpenAI
GPT-4o mini
56/100- ECI126.6
- Price$0.15 / $0.60
- Context128K
Alibaba (Qwen)
Qwen2.5 72B Instruct
40/100- ECI129.0
- Price$1.40 / $5.60
- Context131K
GPT-4o mini is our pick
GPT-4o mini is the better all-round choice, scoring 56/100 against GPT-4o (43) and Qwen2.5 72B Instruct (40). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen2.5 72B InstructCapabilities Index (ECI): Qwen2.5 72B Instruct 129.0 · GPT-4o 129.0 · GPT-4o mini 126.6
- Lowest priceGPT-4o miniGPT-4o mini $0.263 · Qwen2.5 72B Instruct $2.45 · GPT-4o $4.38 per 1M tokens (3:1 blend)
- Longest contextQwen2.5 72B InstructQwen2.5 72B Instruct 131,072 · GPT-4o 128,000 · GPT-4o mini 128,000 tokens
- Widest inputsGPT-4o and GPT-4o miniGPT-4o: Text, Images, PDFs · GPT-4o mini: Text, Images, PDFs · Qwen2.5 72B Instruct: Text
- Self-hostingQwen2.5 72B InstructPublishes downloadable weights
| Measure | Weight | GPT-4o | GPT-4o mini | Qwen2.5 72B Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 52 | 49 | 52 |
| Price | 25% | 19 | 77 | 31 |
| Inputs & features | 15% | 70 | 70 | 25 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 43/100 | 56/100 | 40/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 129.0 | 126.6 | 129.0 (best) |
| ECI rank | #129 of 148 | #135 of 148 | #128 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 48.9% | 37.7% | 49.2% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | 0.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 6.3% | 6.9% | 8.1% (best) |
| SimpleQA VerifiedShort factual questions | — | 8.3% | — |
| Price per million tokens | |||
| Input | $2.50 | $0.15 (best) | $1.40 |
| Output | $10.00 | $0.60 (best) | $5.60 |
| Cached input | $1.25 | $0.075 (best) | — |
| Blended (3:1) | $4.38 | $0.263 (best) | $2.45 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official OpenAI API | Official Alibaba API |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 131,072 tokens (best) |
| Max output | 16,384 tokens (best) | 16,384 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | gpt-4o | gpt-4o-mini | qwen2-5-72b-instruct |
| API providers | 19 | 21 (best) | 1 |
| Released | May 13, 2024 | Jul 18, 2024 | Sep 19, 2024 |
| Knowledge cutoff | Sep 2023 | Sep 2023 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
GPT-4o$45.00
GPT-4o mini$2.70
Qwen2.5 72B Instruct$25.20
Which should you choose?
Which is better: GPT-4o, GPT-4o mini or Qwen2.5 72B Instruct?
GPT-4o mini is the better all-round choice, scoring 56/100 against GPT-4o (43) and Qwen2.5 72B Instruct (40). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-4o, GPT-4o mini or Qwen2.5 72B Instruct?
GPT-4o mini is cheaper at $0.15 input / $0.60 output per million tokens (official OpenAI API price). Qwen2.5 72B Instruct costs $1.40 input / $5.60 output per million tokens (official Alibaba API price); GPT-4o costs $2.50 input / $10.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for GPT-4o mini versus $2.45 for Qwen2.5 72B Instruct (9.3× as much) and $4.38 for GPT-4o (17× as much).
Which scores higher on benchmarks?
Qwen2.5 72B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 72B Instruct 129.0 (#128 of 148), GPT-4o 129.0 (#129 of 148) and GPT-4o mini 126.6 (#135 of 148). The confidence ranges of the top two overlap (123.8–130.7 vs 124.2–131.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen2.5 72B Instruct 49.2%, GPT-4o 48.9%, GPT-4o mini 37.7%; OTIS Mock AIME 2024–2025 — Qwen2.5 72B Instruct 8.1%, GPT-4o mini 6.9%, GPT-4o 6.3%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-4o, GPT-4o mini and Qwen2.5 72B Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 72B Instruct leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen2.5 72B Instruct has the largest context window at 131,072 tokens, against 128,000 for GPT-4o and 128,000 for GPT-4o mini. Maximum output per response: GPT-4o up to 16,384, GPT-4o mini up to 16,384, Qwen2.5 72B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
GPT-4o accepts text, images and PDFs; GPT-4o mini accepts text, images and PDFs; Qwen2.5 72B Instruct accepts text. GPT-4o handles the widest range of inputs.
Are any of these open source?
Qwen2.5 72B Instruct publishes its weights and can be self-hosted; GPT-4o and GPT-4o mini is proprietary.
Which is newer?
Qwen2.5 72B Instruct is the newest, released Sep 19, 2024. GPT-4o mini came out Jul 18, 2024; GPT-4o came out May 13, 2024. Knowledge cutoff: GPT-4o Sep 2023, GPT-4o mini Sep 2023, Qwen2.5 72B Instruct Apr 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.