Nova Pro vs GPT-4o vs Qwen2.5 32B Instruct

Nova Pro is the better all-round choice, scoring 48/100 against GPT-4o (43) and Qwen2.5 32B Instruct (43). It leads on context window. Qwen2.5 32B Instruct wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Qwen2.5 32B Instruct is cheaper at $0.70 input / $2.80 output per million tokens (official Alibaba API price). Nova Pro costs $0.80 input / $3.20 output per million tokens (official Amazon Bedrock 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 $1.23 per million tokens for Qwen2.5 32B Instruct versus $1.40 for Nova Pro (1.1× as much) and $4.38 for GPT-4o (3.6× as much).

GPT-4o scores higher on the Capabilities Index (ECI): GPT-4o 129.0 (#129 of 148), Qwen2.5 32B Instruct 128.5 (#131 of 148) and Nova Pro 123.8 (#137 of 148). The confidence ranges of the top two overlap (124.2–131.5 vs 123.5–130.0), so treat the gap as small.

There are no published SWE-bench Verified results for Nova Pro, GPT-4o and Qwen2.5 32B 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. All three support tool calling for agent workflows.

Nova Pro has the largest context window at 300,000 tokens, against 131,072 for Qwen2.5 32B Instruct and 128,000 for GPT-4o. Maximum output per response: Nova Pro up to 10,000, GPT-4o up to 16,384, Qwen2.5 32B Instruct up to 8,192 tokens.

Nova Pro accepts text, images, PDFs and video; GPT-4o accepts text, images and PDFs; Qwen2.5 32B Instruct accepts text. Nova Pro handles the widest range of inputs.

Qwen2.5 32B Instruct publishes its weights and can be self-hosted; Nova Pro and GPT-4o is proprietary.

Nova Pro is the newest, released Dec 3, 2024. Qwen2.5 32B Instruct came out Sep 17, 2024; GPT-4o came out May 13, 2024. Knowledge cutoff: Nova Pro Oct 2024, GPT-4o Sep 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.