GPT-4o mini vs Llama-3.1-70B-Instruct vs Mistral Large
GPT-4o mini comes out ahead, 55 to 44 and 43 on our weighted score, and it is the cheaper option too.
- Our pick
OpenAIGPT-4o mini
55/100- ECI126.5
- Price$0.15 / $0.60
- Context128K
MetaLlama-3.1-70B-Instruct
43/100- ECI125.9
- Price$0.72 / $0.72
- Context128K
Mistral AIMistral Large
44/100- ECI122.0
- Price$0.50 / $1.50
- Context128K
GPT-4o mini is our pick
GPT-4o mini is the better all-round choice, scoring 55/100 against Mistral Large (44) and Llama-3.1-70B-Instruct (43). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-4o miniCapabilities Index (ECI): GPT-4o mini 126.5 · Llama-3.1-70B-Instruct 125.9 · Mistral Large 122.0
- Lowest priceGPT-4o miniGPT-4o mini $0.263 · Llama-3.1-70B-Instruct $0.72 · Mistral Large $0.75 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGPT-4o mini 128,000 · Llama-3.1-70B-Instruct 128,000 · Mistral Large 128,000 tokens
- Widest inputsGPT-4o miniGPT-4o mini: Text, Images, PDFs · Llama-3.1-70B-Instruct: Text · Mistral Large: Text, PDFs
- Self-hostingLlama-3.1-70B-InstructPublishes downloadable weights
| Measure | Weight | GPT-4o mini | Llama-3.1-70B-Instruct | Mistral Large |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 47 | 47 | 42 |
| Price | 25% | 74 | 54 | 53 |
| Inputs & features | 15% | 70 | 25 | 45 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 55/100 | 43/100 | 44/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-4o miniOpenAI | Llama-3.1-70B-InstructMeta | Mistral LargeMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 126.5 (best) | 125.9 | 122.0 |
| ECI rank | #148 of 165 (best) | #149 of 165 | #153 of 165 |
| GPQA DiamondGraduate-level science questions | 37.7% | 44.2% (best) | 38.8% |
| FrontierMath Tiers 1–3Research-level mathematics | 0.7% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 6.9% (best) | 3.6% | 1.9% |
| SimpleQA VerifiedShort factual questions | 8.3% | — | — |
| Price per million tokens | |||
| Input | $0.15 (best) | $0.72 | $0.50 |
| Output | $0.60 (best) | $0.72 | $1.50 |
| Cached input | $0.075 | — | $0.05 (best) |
| Blended (3:1) | $0.263 (best) | $0.72 | $0.75 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 8 providers | Official Mistral API |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 128,000 tokens |
| Max output | 16,384 tokens | 4,096 tokens | 102,400 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | gpt-4o-mini | — | mistral-large-latest |
| API providers | 26 (best) | 8 | 11 |
| Released | Jul 18, 2024 | Jul 23, 2024 | Feb 26, 2024 |
| Knowledge cutoff | Sep 2023 | Dec 2023 | Nov 30, 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 mini$2.70
- Llama-3.1-70B-Instruct$8.64
- Mistral Large$8.00
Which should you choose?
Which is better: GPT-4o mini, Llama-3.1-70B-Instruct or Mistral Large?
GPT-4o mini is the better all-round choice, scoring 55/100 against Mistral Large (44) and Llama-3.1-70B-Instruct (43). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-4o mini, Llama-3.1-70B-Instruct or Mistral Large?
GPT-4o mini is cheaper at $0.15 input / $0.60 output per million tokens (official OpenAI API price). Llama-3.1-70B-Instruct costs $0.72 input / $0.72 output per million tokens (median across 8 API providers); Mistral Large costs $0.50 input / $1.50 output per million tokens (official Mistral 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 $0.72 for Llama-3.1-70B-Instruct (2.7× as much) and $0.75 for Mistral Large (2.9× as much).
Which scores higher on benchmarks?
GPT-4o mini scores higher on the Capabilities Index (ECI): GPT-4o mini 126.5 (#148 of 165), Llama-3.1-70B-Instruct 125.9 (#149 of 165) and Mistral Large 122.0 (#153 of 165). The confidence ranges of the top two overlap (120.5–128.6 vs 120.8–128.2), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.1-70B-Instruct 44.2%, Mistral Large 38.8%, GPT-4o mini 37.7%; OTIS Mock AIME 2024–2025 — GPT-4o mini 6.9%, Llama-3.1-70B-Instruct 3.6%, Mistral Large 1.9%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-4o mini, Llama-3.1-70B-Instruct and Mistral Large yet, so there is no like-for-like coding score. On overall capability, GPT-4o mini 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?
GPT-4o mini, Llama-3.1-70B-Instruct and Mistral Large share the same 128,000-token context window. Maximum output per response: GPT-4o mini up to 16,384, Llama-3.1-70B-Instruct up to 4,096, Mistral Large up to 102,400 tokens.
Which can read images, PDFs, audio or video?
GPT-4o mini accepts text, images and PDFs; Llama-3.1-70B-Instruct accepts text; Mistral Large accepts text and PDFs. GPT-4o mini 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 mini and Mistral Large is proprietary.
Which is newer?
Llama-3.1-70B-Instruct is the newest, released Jul 23, 2024. GPT-4o mini came out Jul 18, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: GPT-4o mini Sep 2023, Llama-3.1-70B-Instruct Dec 2023, Mistral Large Nov 30, 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 Nov 2, 2026.
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