GPT-5.6 Luna

OpenAIProprietary

The fast, cheap 5.6 tier for high-volume latency-sensitive work — chatbots, classification, realtime pipelines.

Index @ Low

59.0

Context

1.05M

$/M in · out

$1 · $6

Median speed

230 tok/s

Released

Jul 9, 2026

02·Which effort for which task

The sweet spot, per task

Cheapest effort tier that keeps ≥96% of this model's peak quality on the benchmarks behind each task type. Below the floor number, quality is not okay — it just fails quietly.

Everyday writing & Q&A

Medium

Chat, drafting, summaries, general questions.

keeps 97.5% of peak−85% cost

Code assist

High

Autocomplete, single functions, small fixes.

keeps 98.3% of peak−61% cost

Coding agents

High

Real repos, multi-file changes, end-to-end tickets.

keeps 96.5% of peak−61% cost

⚠ at Minimal: only 68% of peak — avoid

Math & quantitative

X-High

Derivations, statistics, financial models.

keeps 100.0% of peakpeak tier needed

⚠ at Minimal: only 52% of peak — avoid

Hard research problems

High

Novel, frontier, genuinely difficult questions.

keeps 96.0% of peak−61% cost

⚠ at Minimal: only 62% of peak — avoid

Agents & tool use

High

Long workflows with tools, policies, and state.

keeps 97.9% of peak−61% cost

03·The effort ladder

Quality and cost, tier by tier

On everyday tasks, Medium keeps 97.5% of X-High quality at $0.013 vs $0.089 per task.

Intelligence Index by effort

Cost per typical task by effort

04·Benchmark detail

Scores at X-High

Minimal Low Medium High X-High

at X-Highat X-High (peak)

Benchmark	X-High	Peak	What it predicts
MMLU-Pro	84.0	84.0	Everyday Q&A · Drafting emails & docs · Summarizing articles
GPQA Diamond	82.0	82.0	Technical analysis · Root-cause debugging · Scientific writing
Humanity's Last Exam	24.0	24.0	Novel research questions · Frontier problem solving
AIME 2025	88.0	88.0	Financial modeling · Statistics · Algorithm design
SWE-bench Verified	72.0	72.0	Coding agents · Bug fixing in real repos · Multi-file refactors
LiveCodeBench	79.0	79.0	Writing functions from scratch · Algorithms · Code autocomplete
τ²-bench	78.0	78.0	Tool-using agents · Customer-facing automation · Multi-step workflows
IFEval	90.0	90.0	Structured output (JSON) · Templated generation · Batch pipelines

06·Drift

Is it still the same model this week?

Weekly Intelligence Index · dashed rules mark serving-change events

No serving-change events detected for GPT-5.6 Luna in the tracked window.

07·Call it

One key, this model, your effort

The gateway speaks the OpenAI Chat Completions dialect. Pick a host with gpt-5.6-luna@host syntax, set reasoning_effort, and the sweet spot above becomes one line of config. Full docs →

chat with GPT-5.6 Luna

curl https://models.fyi/api/v1/chat/completions \
  -H "Authorization: Bearer $MFYI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.6-luna",
    "reasoning_effort": "medium",
    "messages": [{"role": "user", "content": "Hello"}]
  }'
# local dev: replace https://models.fyi with http://localhost:3000