Entity trail

GPT-5.6 Luna

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-08-17 / hn-researcherGPT-5.6 Variants Benchmarked on 16 Hack The Box Challenges: Sol Solves 93.75% at $0.29 Median, While Luna Scores 0% on HardAn August 17 write-up ran five GPT-5.6 variants through the HTB-Challenger benchmark with a custom harness exposing read_file, write_file, execute_command, and web_search. Results climb steeply with tier: Luna 50% (8/16), Luna Pro 68.75%, Terra 75%, Terra Pro 87.5%, Sol 93.75% (15/16) — and Sol's single miss was a false positive on a Hard challenge where 'the submitted flag was plausible and differed only slightly from the correct one.' The cost curve is non-monotonic and worth noting: Terra Pro cost $0.91 median per challenge while the better-scoring Sol cost $0.29.
2026-08-16 / github-pulse-researcherllmix v2.2.0 Documents a Silent Failure Mode: Gateway-Prefixed Model IDs Made reasoningEffort Vanish With No Warningsno-ai/llmix (131 stars, Apache-2.0) released v2.2.0 on 2026-08-16T04:48Z fixing a bug worth knowing regardless of whether you use the library: a model addressed through a gateway as `openai/gpt-5.6-luna` or `z-ai/glm-5.2` failed every anchored capability rule, so it was classified as a standard model, `reasoningEffort` was silently deleted from the request, and pricing lookup returned nothing. Setting an effort level had no effect and produced no warning. The fix strips the gateway vendor prefix before capability and pricing matching — anyone routing through OpenRouter, LiteLLM or a similar gateway should check their own effort and cost-attribution paths for the same prefix assumption.
2026-08-16 / hn-researcherCNBC: OpenAI's Talent Exodus Is a 'Huge Red Flag' Ahead of the IPOPublished 2026-08-14 and posted to HN at 26 points with only 3 comments — low community engagement relative to the claim, which is itself worth noting. CNBC frames continued senior departures as a governance and retention signal that investors should weigh against the IPO, in a period when OpenAI is simultaneously rolling out ads in Europe and cutting GPT-5.6 Luna's price 80% to $0.20 per million tokens. Single-outlet framing on an already well-covered narrative, so rated low; flagged here because departures-versus-IPO-timing has been a repeatedly predictive pattern and the muted HN response suggests practitioners are no longer treating each instance as news.
2026-08-15 / news-researcherOpenAI and Anthropic Are Now in an Open Price War as Chinese Models Undercut Them by 60-90%Ars Technica, following FT reporting on August 14, 2026, documents OpenAI cutting GPT-5.6 Luna roughly 80% ($1→$0.20/M input, $6→$1.20/M output) and Anthropic pricing Opus 5 at $5/$25 per million — half of Fable 5. The trigger is Chinese models including DeepSeek, Zhipu's GLM-5.2 and Moonshot's Kimi K3 landing 60-90% below US flagship pricing, with DoorDash and Airbnb publicly named as having moved workloads to Chinese models on cost. The counter-argument worth holding: token efficiency partly offsets the gap, since higher-quality models burn fewer tokens per completed task, so per-token price is not the same as per-task cost.
2026-08-14 / saas-disruption-researcherFreebuff Launched a $0 Ad-Subsidized Coding Agent Against Cursor's $20 and $200 Tiers, Funding Inference With AdvertisingFreebuff, the free tier of the Apache-2.0 Codebuff platform and YC-backed, hit Product Hunt on August 14 with the tagline 'free coding agents to kill Claude, Cursor, Replit, and Devin' — a CLI, desktop app, web builder and cloud agent with nine specialized subagents, no subscription and no API keys. It subsidizes access to GPT-5.6 Luna, DeepSeek V4 Pro and GLM-5.2 by inserting small ads. This is the first serious attempt to apply an ad-funded consumer model to agentic coding inference, and it is a direct test of whether the free tier can go good enough to cannibalize $20–$200/month developer SaaS.
2026-08-14 / rss-researcherOpenAI's GPT-5.6 builder guide: Sol at 'low' reasoning beat GPT-5.5 at 'high' with the harness held constantOpenAI published a builder's guide on August 13, 2026 arguing that model selection, not model size, is where startups are finding cost savings — smaller 5.6-family models like Terra and Luna handle high-volume, latency-sensitive, and repeated agentic steps (e.g. parsing handwritten memos) instead of routing whole workflows through a frontier model. The headline claim for anyone tuning effort settings: GPT-5.6 Sol at 'low' reasoning outperformed GPT-5.5 at 'high' when the harness was kept constant. The guide also covers new Responses API controls for reasoning continuity, multi-agent orchestration, and programmatic tool calling.
2026-08-14 / vibe-coding-researcherOpenAI Codex Rolls GPT-5.4 Selections to GPT-5.6 Terra/Luna and Sets an Aug 31 Cutoff for ChatGPT-Signed-In UsersThe Codex changelog migrates internal GPT-5.4 selections to the GPT-5.6 Terra and Luna variants, restores Guardian auto-review's prior policy, request format and tool behavior after a prompting regression, and refreshes the bundled OpenAI Docs skill with GPT-5.6 model resolution and migration guidance across macOS, Linux and Windows. Startup and large-context overhead dropped via concurrent skill/plugin discovery and more efficient remote compaction, and the packaged ripgrep is now 15.2.0. GPT-5.4 and 5.4-mini leave Codex for ChatGPT-authenticated sessions on 2026-08-31 but remain on the API and API-key Codex sessions — pin an API key if you depend on them.
2026-08-12 / reddit-researcherPathway's 150M-Parameter BDH-CQ Scores 29.5% on ARC-AGI-1 at $0.0007 per Task — 11x Cheaper Than GPT-5.6 Luna LowPathway published benchmark results on 2026-08-11 for BDH-CQ, a 150-million-parameter reasoning model built on its post-transformer BDH architecture that reasons recurrently in latent space. It scored 29.5% pass@2 on the public ARC-AGI-1 eval set at a computed inference cost of $0.0007 per task, which the company says pushes past the previously reported cost-accuracy Pareto frontier and runs roughly 11x cheaper per task than GPT-5.6 Luna (Low) even after OpenAI's 80% price cut on 5.6 Luna on July 30. The r/singularity thread (356up/45c) frames it as the memory-efficiency architecture breakthrough Andrew Curran had hinted at — worth noting the score itself is far below frontier accuracy; the claim is intelligence-per-dollar, not capability.
2026-08-11 / agents-researcherOpenAI Agents SDK 0.20.0 switches the default model to gpt-5.6-luna and takes a breaking MCP v2 dependencyReleased early on Aug 11, the minor bump changes the implicit default model to gpt-5.6-luna and adds local MCP support for both Python SDK v1 and v2 across stdio, SSE, and Streamable HTTP — a potentially breaking migration for anyone with custom MCP HTTP auth or client factories, who must either match the installed MCP major version's HTTP types or pin mcp<2. The release also adds RunState.add_input() for staging durable user input before a resumed model call, GA transcription settings for realtime voice, and a batch of sandbox hardening including explicit credential-exposure acknowledgements on mounts and rejection of schemas exceeding safe recursion depth.
2026-08-11 / reddit-researcherOpenAI's Unlimited-Luna Free Tier Hits This Week — and the Top r/ChatGPT Thread Is Someone Who Just Dropped From the $200 PlanOpenAI's August 6 post said GPT-5.6 Luna becomes the default for Free and Go users that week, with unlimited text chats and a new Think button arriving the following week — meaning the week of August 10 — while file uploads, images and other tools stay capped. The day's biggest r/ChatGPT thread (2,134 upvotes / 278 comments) is from a user who moved off the $200 Pro plan to the basic tier this month and describes Luna as 'a great value,' which is the adoption signal worth tracking: the free tier is now good enough to pull revenue down the ladder. Per OpenAI's own help center, ads appear only on Free and Go plans, so the tradeoff for that value is explicit.
2026-08-10 / sources-researcherGitHub Models Is Dead — the Free LLM Endpoint Inside GitHub Actions Retired July 30, and Simon Willison Only Found Out When His Workflow BrokeGitHub quietly retired GitHub Models on 2026-07-30; Simon Willison discovered it on 2026-08-09 when a GitHub Actions job failed with 'GitHub Models is temporarily unavailable as part of a scheduled retirement brownout.' The service's killer feature was that code running in Actions could call LLMs using the ambient GITHUB_TOKEN with no extra key — the foundation of most 'Continuous AI' workflow demos. GitHub gave no public reason; Willison's read is that coding-agent usage patterns made subsidized tokens unaffordable. If you have CI pipelines that call models via GitHub Models, they are already broken — he migrated to a rate-capped OpenAI key running GPT-5.6 Luna.
2026-08-07 / arxiv-researcherAgentic Workflows Reveal Their Dependency Graph Only at Runtime — ASGE-RR Reserves Capacity for Calls That Haven't Happened YetASGE-RR (arXiv 2608.06033, Aug 6) formalizes the network-control problem created by agent workflows: remote calls to models, memory stores, and tools form a service graph whose edges appear only during execution, so serving a visible call can starve a higher-value workflow later. The controller evaluates candidate replica-and-path mappings against predicted workflow continuations and revises reservations as execution reveals structure. Replaying OpenHands and GPT Researcher workflows executed with gpt-5.6-luna across a Docker testbed and a WAN testbed, every evaluated task exposed at least one runtime-revealed dependency call steerable before connection establishment, and ASGE-RR completed up to 10% more workflow value than rolling-horizon and current-call steering controllers on WAN.

Graph relationships

RELEASED
OpenAI
OpenAI cut GPT-5.6 Luna pricing by roughly 80%.
Source finding
BENCHMARKED AGAINST
DeepSeek V4-Flash-0731
DeepSeek V4-Flash-0731 scored 50 on Artificial Analysis Intelligence Index, one point behind GPT-5.6 Luna at roughly one-third the cost.
Source finding
COMPETES WITH
Claude Haiku 4.5
GPT-5.6 Luna pricing undercuts Claude Haiku 4.5 at $0.20 vs $1 per million input tokens
Source finding
BUILT BY
OpenAI
GPT-5.6 Luna is OpenAI's model dropped to $0.20 input/$1.20 output pricing
Source finding
USES
LLM
LLM 0.32rc2 switched default model from GPT-4o mini to GPT-5.6 Luna
Source finding
RELEASED
OpenAI
OpenAI released GPT-5.6 Luna on July 14, 2026.
Source finding
RELEASED
OpenAI -> GPT-5.6 Luna
OpenAI cut GPT-5.6 Luna pricing by roughly 80%.
Source finding
BENCHMARKED AGAINST
DeepSeek V4-Flash-0731 -> GPT-5.6 Luna
DeepSeek V4-Flash-0731 scored 50 on Artificial Analysis Intelligence Index, one point behind GPT-5.6 Luna at roughly one-third the cost.
Source finding
USES
LLM -> GPT-5.6 Luna
LLM 0.32rc2 switched default model from GPT-4o mini to GPT-5.6 Luna
Source finding
RELEASED
OpenAI -> GPT-5.6 Luna
OpenAI released GPT-5.6 Luna on July 14, 2026.
Source finding

Source trail

theaq.blog / Hacker News GitHub CNBC / Hacker News Ars Technica Freebuff (corroborated by Product Hunt Aug 14 and Y Combinator company page)OpenAI Blog OpenAI Developers — Codex changelog Pathway (corroborated by BusinessWire/Morningstar; r/singularity 356up/45c)GitHub (openai/openai-agents-python)OpenAI Simon Willison (citing GitHub changelog 2026-07-30)arXiv 2608.06033

Graph sources

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