GPT-4o vs Llama-3.1-70B-Instruct
Too close to call on our weighted score (Llama-3.1-70B-Instruct 44, GPT-4o 43). 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
Add a model
Make it a three-way comparison.
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), so choose by what matters most for your work: GPT-4o for raw capability and Llama-3.1-70B-Instruct on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-4oCapabilities Index (ECI): GPT-4o 129.0 · Llama-3.1-70B-Instruct 125.9
- Lowest priceLlama-3.1-70B-InstructLlama-3.1-70B-Instruct $0.72 · GPT-4o $4.38 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGPT-4o 128,000 · Llama-3.1-70B-Instruct 128,000 tokens
- Widest inputsGPT-4oGPT-4o: Text, Images, PDFs · Llama-3.1-70B-Instruct: Text
- Self-hostingLlama-3.1-70B-InstructPublishes downloadable weights
| Measure | Weight | GPT-4o | Llama-3.1-70B-Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 52 | 48 |
| Price | 25% | 19 | 57 |
| Inputs & features | 15% | 70 | 25 |
| Context window | 10% | 24 | 24 |
| Overall | 100% | 43/100 | 44/100 |
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 |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 129.0 (best) | 125.9 |
| ECI rank | #129 of 148 (best) | #136 of 148 |
| GPQA DiamondGraduate-level science questions | 48.9% (best) | 44.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 6.3% (best) | 3.6% |
| Price per million tokens | ||
| Input | $2.50 | $0.72 (best) |
| Output | $10.00 | $0.72 (best) |
| Cached input | $1.25 | — |
| Blended (3:1) | $4.38 | $0.72 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 5 providers |
| Limits | ||
| Context window | 128,000 tokens | 128,000 tokens |
| Max output | 16,384 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | Yes | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | gpt-4o | — |
| API providers | 19 (best) | 5 |
| Released | May 13, 2024 | Jul 23, 2024 |
| Knowledge cutoff | Sep 2023 | Dec 2023 |
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
Which should you choose?
Which is better: GPT-4o or Llama-3.1-70B-Instruct?
It is close. Our weighted score puts them within a point (Llama-3.1-70B-Instruct 44/100, GPT-4o 43/100), so choose by what matters most for your work: GPT-4o 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 or Llama-3.1-70B-Instruct?
Llama-3.1-70B-Instruct is cheaper at $0.72 input / $0.72 output per million tokens (median across 5 API providers). 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 $4.38 for GPT-4o (6.1× as much).
Which scores higher on benchmarks?
GPT-4o scores higher on the Capabilities Index (ECI): 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 (124.2–131.5 vs 121.0–128.1), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4o 48.9%, Llama-3.1-70B-Instruct 44.2%; OTIS Mock AIME 2024–2025 — 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 and Llama-3.1-70B-Instruct yet, so there is no like-for-like coding score. On overall capability, GPT-4o leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
GPT-4o and Llama-3.1-70B-Instruct share the same 128,000-token context window. Maximum output per response: GPT-4o up to 16,384, Llama-3.1-70B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
GPT-4o accepts text, images and PDFs; Llama-3.1-70B-Instruct accepts text. GPT-4o handles the widest range of inputs.
Are any of these open source?
Llama-3.1-70B-Instruct publishes its weights and can be self-hosted; GPT-4o is proprietary.
Which is newer?
Llama-3.1-70B-Instruct is the newest, released Jul 23, 2024. GPT-4o came out May 13, 2024. Knowledge cutoff: GPT-4o Sep 2023, Llama-3.1-70B-Instruct Dec 2023.
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.
Related comparisons
- Add Qwen2.5 72B InstructThree-way comparison
- GPT-4o vs Qwen2.5 72B InstructAlibaba (Qwen) · ECI 129.0
- GPT-4o vs Mistral Large 2.1Mistral AI · ECI 128.5
- GPT-4o vs Claude Sonnet 3.5 v2Anthropic · ECI 133.5
- Llama-3.1-70B-Instruct vs GPT-4o miniOpenAI · ECI 126.6
- Llama-3.1-70B-Instruct vs Qwen2.5 32B InstructAlibaba (Qwen) · ECI 128.5
- Llama-3.1-70B-Instruct vs Nova ProAmazon · ECI 123.8
