Prices as of 2026-07-14 · rev 179affb· unknown is shown as unknown, never $0.00
Pricing
| Input · fresh prompt tokens | $5.50 / M |
|---|---|
| Output · generated tokens | $33.00 / M |
| Cache read · cached-input hit | $0.55 / M |
| Cache write · cache creation | unknown |
| Reasoning · thinking tokens | unknown |
Context-length tiers
| Base (≤ 272K) | $5.50 / $33.00 per M |
|---|---|
| Above 272K | $11.00 / $49.50 per M |
When total input exceeds the threshold, the tier rate applies to the whole request.
Cross the 272K line by a single token and the whole request reprices — every token, not just those above the line. Assumes 500 output tokens (the cliff's position depends on input alone). Snapshot rates; providers do change tier structure.
Reasoning tokens: no separate rate is published. Providers typically bill thinking tokens at the output rate ($33.00 / M) — which is what the estimator assumes, so an extended-thinking workload isn't silently undercounted.
Model info
- Provider
- Azure OpenAI
- Catalog key
- azure/azure/eu/gpt-5.6
- Identifier
- Floating alias (may re-point over time)
- Type
- Chat
- Max input
- 1,050,000 tokens
- Max output
- 128,000 tokens
- Released
- 2026-07-09
- Knowledge cutoff
- 2026-02-16
- Weights
- Proprietary
- Price snapshot
- 2026-07-14 · rev 179affb
Pricing from TokenTriage's resolved price artifact (TokenTriage resolved price artifact (internal/pricing/data/prices.json)); capability + model metadata is third-party (LiteLLM model_prices_and_context_window.json, models.dev). Unknown means unstated, not absent.
Effective cost / 1,000 words
normalised comparison metric · your headline price is per token, but tokenizers pack words differentlygpt-5.6 uses the OpenAI o200k (GPT-4o / GPT-4.1 / o-series) tokenizer. The figures below multiply its per-token price by how many tokens that tokenizer produces for representative text — so two models at the samelist price aren't the same price per word. This is a comparison lens, not a bill:the estimator remains the authoritative cost for your own traffic.
⚠ The OpenAI o200k (GPT-4o / GPT-4.1 / o-series) tokenizer is inferred from OpenAI's current base encoding for this model — not independently confirmed. If it ships a different tokenizer, its per-word figures would shift.
Among 75 models with a public tokenizer, GPT 5.6 ranks 55th by list price per token and 55th by cost per 1,000 words — normalising doesn't change its position here.
Among 75 models with a public tokenizer, GPT 5.6 ranks 55th by list price per token and 55th by cost per 1,000 words — normalising doesn't change its position here.
Among 75 models with a public tokenizer, GPT 5.6 ranks 55th by list price per token and 55th by cost per 1,000 words — normalising doesn't change its position here.
Tokens/word measured with gpt-tokenizer (MIT) over a fixed self-authored corpus (as of 2026-07-29); only derived counts are stored, no vocabulary is shipped. Word count: whitespace-delimited tokens; approximate for non-spaced scripts (CJK) in the multilingual sample.Models whose tokenizer isn't publicly reproducible (e.g. Claude, Gemini) are not comparable here and are excluded — never assigned a guessed count.
Capabilities
9 documented as supportedInput & output
API behaviour
Agents & tools
✓ supported ·✕ not supported ·? not documented ·⚠ sources disagree. A models.dev tag means the LiteLLM catalog was silent and an independent source supplied the value (lower confidence); ? is never silently turned into a confident ✕.
Estimate a request
disjoint token buckets · input = fresh (uncached) tokensHow output length drives the bill
at a 1K-token prompt · cost scales linearly with outputOutput tokens overtake input spend at ~167 tokens for this model — past that, generation is your bill, whatever the headline input price says. Computed by the same cost engine as the estimate above.
Route to GPT 5.6
OpenAI-compatible · one base URLcurl https://YOUR-TOKENTRIAGE-HOST/v1/chat/completions \ -H "Authorization: Bearer $TOKENTRIAGE_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "azure/azure/eu/gpt-5.6", "messages": [{"role": "user", "content": "Hello"}] }'from openai import OpenAI client = OpenAI( base_url="https://YOUR-TOKENTRIAGE-HOST/v1", api_key="YOUR_TOKENTRIAGE_KEY", ) resp = client.chat.completions.create( model="azure/azure/eu/gpt-5.6", messages=[{"role": "user", "content": "Hello"}], ) print(resp.choices[0].message.content)
Point your existing OpenAI client at your TokenTriage host and pass the catalog key as the model. TokenTriage attributes the real cost per request and can route to a cheaper model once it's proven just as good on your traffic.
Data & API
machine-readable · rev 179affbPull this model's pricing, capabilities, benchmarks and cross-source provenance programmatically — every field carries the snapshot rev, and unknown is null, never 0. Free to reuse with attribution: benchmarks & Capabilities Index © Epoch AI (CC-BY (Epoch AI)); human-preference Elo © LMArena (CC-BY-4.0); capability & price cross-check via models.dev v2 (MIT) · Portkey (MIT) · TrueFoundry (MIT); open-weights facts via Hugging Face (per-repo license).
A price is a guess until it meets your traffic.
This page tells you what GPT 5.6 charges per token. TokenTriage tells you what it costs on your real requests — and cuts the bill only after proving a cheaper model is just as good.