GPT-5.2 vs Inkling

It is close. Our weighted score puts them within 2 points (GPT-5.2 61/100, Inkling 59/100), so choose by what matters most for your work: GPT-5.2 for raw capability and Inkling for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

GPT-5.2 is cheaper at $1.75 input / $14.00 output per million tokens (official OpenAI API price). Inkling costs $3.74 input / $9.36 output per million tokens (official Thinking Machines API price). At a typical mix of three input tokens to one output token, that is $4.81 per million tokens for GPT-5.2 versus $5.14 for Inkling (1.1× as much).

GPT-5.2 scores higher on the Capabilities Index (ECI): GPT-5.2 153.5 (#38 of 148) and Inkling 148.6 (#57 of 148). Their confidence ranges do not overlap (151.7–155.4 vs 145.7–150.6), so the gap is a real one. On individual benchmarks: GPQA Diamond — GPT-5.2 91.4%, Inkling 88.3%; FrontierMath Tiers 1–3 — GPT-5.2 67.4%, Inkling 33.3%; OTIS Mock AIME 2024–2025 — GPT-5.2 96.1%, Inkling 88.9%; SimpleQA Verified — Inkling 40.3%, GPT-5.2 37.1%.

There are no published SWE-bench Verified results for Inkling yet, so there is no like-for-like coding score. On overall capability, GPT-5.2 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Inkling has the largest context window at 1,048,576 tokens, against 400,000 for GPT-5.2. Maximum output per response: GPT-5.2 up to 128,000, Inkling up to 1,048,576 tokens.

GPT-5.2 accepts text and images; Inkling accepts text, images and audio. Inkling handles the widest range of inputs.

Inkling publishes its weights (Apache-2.0) and can be self-hosted; GPT-5.2 is proprietary.

Inkling is the newest, released Jul 15, 2026. GPT-5.2 came out Dec 11, 2025. Knowledge cutoff: GPT-5.2 Aug 31, 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 Oct 4, 2026.