Llama-3.1-8B-Instruct vs Solar Pro 2 vs Qwen2.5 7B Instruct

It is close. Our weighted score puts them within a point (Qwen2.5 7B Instruct 62/100, Llama-3.1-8B-Instruct 62/100, Solar Pro 2 51/100), so choose by what matters most for your work: Qwen2.5 7B Instruct on price and Qwen2.5 7B Instruct for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Qwen2.5 7B Instruct is cheaper at $0.05 input / $0.10 output per million tokens (median across 3 API providers). Llama-3.1-8B-Instruct costs $0.06 input / $0.08 output per million tokens (median across 17 API providers); Solar Pro 2 costs $0.25 input / $0.25 output per million tokens (official Upstage API price). At a typical mix of three input tokens to one output token, that is $0.063 per million tokens for Qwen2.5 7B Instruct versus $0.065 for Llama-3.1-8B-Instruct (1× as much) and $0.25 for Solar Pro 2 (4× as much).

There is no independent benchmark that covers all three models yet. Llama-3.1-8B-Instruct has an ECI of 116.4, Solar Pro 2 has not been scored yet and Qwen2.5 7B Instruct has an ECI of 118.5.

There are no published SWE-bench Verified results for Llama-3.1-8B-Instruct, Solar Pro 2 and Qwen2.5 7B Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Qwen2.5 7B Instruct has the largest context window at 131,072 tokens, against 128,000 for Llama-3.1-8B-Instruct and 65,536 for Solar Pro 2. Maximum output per response: Llama-3.1-8B-Instruct up to 4,096, Solar Pro 2 up to 8,192, Qwen2.5 7B Instruct up to 8,192 tokens.

Llama-3.1-8B-Instruct accepts text; Solar Pro 2 accepts text; Qwen2.5 7B Instruct accepts text. They handle the same number of input types.

Llama-3.1-8B-Instruct and Qwen2.5 7B Instruct publishes its weights (Apache 2.0) and can be self-hosted; Solar Pro 2 is proprietary.

Solar Pro 2 is the newest, released May 20, 2025. Qwen2.5 7B Instruct came out Sep 19, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Llama-3.1-8B-Instruct Dec 2023, Solar Pro 2 Mar 2025.

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.