GPT-4o mini vs Llama-3.1-70B-Instruct vs Qwen2.5 32B Instruct

GPT-4o mini is the better all-round choice, scoring 56/100 against Llama-3.1-70B-Instruct (44) and Qwen2.5 32B Instruct (43). It leads on price and inputs & features. Qwen2.5 32B Instruct wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

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 5 API providers); Qwen2.5 32B Instruct costs $0.70 input / $2.80 output per million tokens (official Alibaba 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 $1.23 for Qwen2.5 32B Instruct (4.7× as much).

Qwen2.5 32B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 32B Instruct 128.5 (#131 of 148), GPT-4o mini 126.6 (#135 of 148) and Llama-3.1-70B-Instruct 125.9 (#136 of 148). The confidence ranges of the top two overlap (123.5–130.0 vs 120.5–128.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen2.5 32B Instruct 46.1%, Llama-3.1-70B-Instruct 44.2%, GPT-4o mini 37.7%; OTIS Mock AIME 2024–2025 — Qwen2.5 32B Instruct 7.4%, GPT-4o mini 6.9%, Llama-3.1-70B-Instruct 3.6%.

There are no published SWE-bench Verified results for GPT-4o mini, Llama-3.1-70B-Instruct and Qwen2.5 32B Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 32B Instruct leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Qwen2.5 32B Instruct has the largest context window at 131,072 tokens, against 128,000 for GPT-4o mini and 128,000 for Llama-3.1-70B-Instruct. Maximum output per response: GPT-4o mini up to 16,384, Llama-3.1-70B-Instruct up to 4,096, Qwen2.5 32B Instruct up to 8,192 tokens.

GPT-4o mini accepts text, images and PDFs; Llama-3.1-70B-Instruct accepts text; Qwen2.5 32B Instruct accepts text. GPT-4o mini handles the widest range of inputs.

Llama-3.1-70B-Instruct and Qwen2.5 32B Instruct publishes its weights and can be self-hosted; GPT-4o mini is proprietary.

Qwen2.5 32B Instruct is the newest, released Sep 17, 2024. Llama-3.1-70B-Instruct came out Jul 23, 2024; GPT-4o mini came out Jul 18, 2024. Knowledge cutoff: GPT-4o mini Sep 2023, Llama-3.1-70B-Instruct Dec 2023, Qwen2.5 32B Instruct Apr 2024.

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.