GPT-5.5 Instant vs Inkling

Inkling is the better all-round choice, scoring 59/100 against GPT-5.5 Instant (51). It leads on capability, price and context window. GPT-5.5 Instant wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Inkling is cheaper at $3.74 input / $9.36 output per million tokens (official Thinking Machines API price). GPT-5.5 Instant costs $5.00 input / $30.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $5.14 per million tokens for Inkling versus $11.25 for GPT-5.5 Instant (2.2× as much).

Inkling scores higher on the Capabilities Index (ECI): Inkling 148.6 (#57 of 148) and GPT-5.5 Instant 142.5 (#89 of 148). Their confidence ranges do not overlap (145.7–150.6 vs 140.0–145.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — Inkling 88.3%, GPT-5.5 Instant 82.5%; FrontierMath Tiers 1–3 — Inkling 33.3%, GPT-5.5 Instant 26.3%; OTIS Mock AIME 2024–2025 — Inkling 88.9%, GPT-5.5 Instant 68.1%.

There are no published SWE-bench Verified results for GPT-5.5 Instant and Inkling yet, so there is no like-for-like coding score. On overall capability, Inkling 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-5.5 Instant. Maximum output per response: GPT-5.5 Instant up to 128,000, Inkling up to 1,048,576 tokens.

GPT-5.5 Instant accepts text, images and PDFs; Inkling accepts text, images and audio. They handle the same number of input types.

Inkling publishes its weights (Apache-2.0) and can be self-hosted; GPT-5.5 Instant is proprietary.

Inkling is the newest, released Jul 15, 2026. GPT-5.5 Instant came out May 5, 2026. Knowledge cutoff: GPT-5.5 Instant Dec 1, 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.