GPT-4o vs Llama-3.1-70B-Instruct vs Qwen2.5 72B Instruct
Too close to call on our weighted score (Llama-3.1-70B-Instruct 44, GPT-4o 43, Qwen2.5 72B Instruct 40). The right pick depends on what you value most.
OpenAIGPT-4o
43/100- ECI129.0
- Price$2.50 / $10.00
- Context128K
MetaLlama-3.1-70B-Instruct
44/100- ECI125.9
- Price$0.72 / $0.72
- Context128K
Alibaba (Qwen)Qwen2.5 72B Instruct
40/100- ECI129.0
- Price$1.40 / $5.60
- Context131K
Too close to call
It is close. Our weighted score puts them within a point (Llama-3.1-70B-Instruct 44/100, GPT-4o 43/100, Qwen2.5 72B Instruct 40/100), so choose by what matters most for your work: Qwen2.5 72B Instruct for raw capability and Llama-3.1-70B-Instruct 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 · Llama-3.1-70B-Instruct 125.9
- Lowest priceLlama-3.1-70B-InstructLlama-3.1-70B-Instruct $0.72 · 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 · Llama-3.1-70B-Instruct 128,000 tokens
- Widest inputsGPT-4oGPT-4o: Text, Images, PDFs · Llama-3.1-70B-Instruct: Text · Qwen2.5 72B Instruct: Text
- Self-hostingLlama-3.1-70B-Instruct and Qwen2.5 72B InstructPublishes downloadable weights
| Measure | Weight | GPT-4o | Llama-3.1-70B-Instruct | Qwen2.5 72B Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 52 | 48 | 52 |
| Price | 25% | 19 | 57 | 31 |
| Inputs & features | 15% | 70 | 25 | 25 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 43/100 | 44/100 | 40/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-4oOpenAI | Llama-3.1-70B-InstructMeta | Qwen2.5 72B InstructAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 129.0 | 125.9 | 129.0 (best) |
| ECI rank | #129 of 148 | #136 of 148 | #128 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 48.9% | 44.2% | 49.2% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 6.3% | 3.6% | 8.1% (best) |
| Price per million tokens | |||
| Input | $2.50 | $0.72 (best) | $1.40 |
| Output | $10.00 | $0.72 (best) | $5.60 |
| Cached input | $1.25 | — | — |
| Blended (3:1) | $4.38 | $0.72 (best) | $2.45 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 5 providers | Official Alibaba API |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 131,072 tokens (best) |
| Max output | 16,384 tokens (best) | 4,096 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | gpt-4o | — | qwen2-5-72b-instruct |
| API providers | 19 (best) | 5 | 1 |
| Released | May 13, 2024 | Jul 23, 2024 | Sep 19, 2024 |
| Knowledge cutoff | Sep 2023 | Dec 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
- Llama-3.1-70B-Instruct$8.64
- Qwen2.5 72B Instruct$25.20
Which should you choose?
Which is better: GPT-4o, Llama-3.1-70B-Instruct or Qwen2.5 72B Instruct?
It is close. Our weighted score puts them within a point (Llama-3.1-70B-Instruct 44/100, GPT-4o 43/100, Qwen2.5 72B Instruct 40/100), so choose by what matters most for your work: Qwen2.5 72B Instruct for raw capability and Llama-3.1-70B-Instruct on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-4o, Llama-3.1-70B-Instruct or Qwen2.5 72B Instruct?
Llama-3.1-70B-Instruct is cheaper at $0.72 input / $0.72 output per million tokens (median across 5 API providers). 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 $0.72 per million tokens for Llama-3.1-70B-Instruct versus $2.45 for Qwen2.5 72B Instruct (3.4× as much) and $4.38 for GPT-4o (6.1× 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 Llama-3.1-70B-Instruct 125.9 (#136 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%, Llama-3.1-70B-Instruct 44.2%; OTIS Mock AIME 2024–2025 — Qwen2.5 72B Instruct 8.1%, GPT-4o 6.3%, Llama-3.1-70B-Instruct 3.6%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-4o, Llama-3.1-70B-Instruct 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 Llama-3.1-70B-Instruct. Maximum output per response: GPT-4o up to 16,384, Llama-3.1-70B-Instruct up to 4,096, Qwen2.5 72B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
GPT-4o accepts text, images and PDFs; Llama-3.1-70B-Instruct accepts text; Qwen2.5 72B Instruct accepts text. GPT-4o handles the widest range of inputs.
Are any of these open source?
Llama-3.1-70B-Instruct and Qwen2.5 72B Instruct publishes its weights and can be self-hosted; GPT-4o is proprietary.
Which is newer?
Qwen2.5 72B Instruct is the newest, released Sep 19, 2024. Llama-3.1-70B-Instruct came out Jul 23, 2024; GPT-4o came out May 13, 2024. Knowledge cutoff: GPT-4o Sep 2023, Llama-3.1-70B-Instruct Dec 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.
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