GPT-5 Nano vs Seed-OSS-36B-Instruct

GPT-5 Nano is the better all-round choice, scoring 70/100 against Seed-OSS-36B-Instruct (60). It leads on capability and inputs & features. Seed-OSS-36B-Instruct wins on context window. The score weighs capability 67%, inputs & features 20%, context window 13%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Seed-OSS-36B-Instruct has no Capabilities Index score yet.

GPT-5 Nano is cheaper at $0.05 input / $0.40 output per million tokens (official OpenAI API price). . At a typical mix of three input tokens to one output token, that is $0.138 per million tokens for GPT-5 Nano versus . Seed-OSS-36B-Instruct has no published per-token price.

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): GPT-5 Nano 75.3% and Seed-OSS-36B-Instruct 69.5%. On individual benchmarks: GPQA Diamond — Seed-OSS-36B-Instruct 71.5%, GPT-5 Nano 69.4%; OTIS Mock AIME 2024–2025 — GPT-5 Nano 81.1%, Seed-OSS-36B-Instruct 67.5%.

There are no published SWE-bench Verified results for GPT-5 Nano and Seed-OSS-36B-Instruct yet, so there is no like-for-like coding score. On overall capability, GPT-5 Nano leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Seed-OSS-36B-Instruct has the largest context window at 524,288 tokens, against 400,000 for GPT-5 Nano. Maximum output per response: GPT-5 Nano up to 128,000, Seed-OSS-36B-Instruct up to 524,288 tokens.

GPT-5 Nano accepts text and images; Seed-OSS-36B-Instruct accepts text. GPT-5 Nano handles the widest range of inputs.

Seed-OSS-36B-Instruct publishes its weights (Apache 2.0) and can be self-hosted; GPT-5 Nano is proprietary.

Seed-OSS-36B-Instruct is the newest, released Aug 20, 2025. GPT-5 Nano came out Aug 7, 2025. Knowledge cutoff: GPT-5 Nano May 30, 2024, Seed-OSS-36B-Instruct Jul 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 Nov 2, 2026.