Pick Claude Fable 5 for the hardest reasoning and most complex problems or long-horizon, multi-step agentic work. Pick GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation or fast, affordable execution while keeping respectable coding. On a tight budget at scale, GPT-5.6 Luna is the value pick.
Claude Fable 5 (Anthropic) and GPT-5.6 Luna (OpenAI) are two of the models people most often weigh against each other in 2026. Claude Fable 5 is anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive. GPT-5.6 Luna is the budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Price: GPT-5.6 Luna is about 10× cheaper on input ($1/$6 per 1M tokens vs $10/$50 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: GPT-5.6 Luna is the newer model by about 30 days (released July 9, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Claude Fable 5
GPT-5.6 Luna
Provider
Anthropic (US)
OpenAI (US)
Released
June 9, 2026
July 9, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$10/$50 per 1M tokens
$1/$6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
The hardest reasoning and most complex problems: Claude Fable 5 — A core design strength of Claude Fable 5.
Long-horizon, multi-step agentic work: Claude Fable 5 — A core design strength of Claude Fable 5.
Frontier-level analysis and research: Claude Fable 5 — A core design strength of Claude Fable 5.
Cheapest GPT-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Fast, affordable execution while keeping respectable coding: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Same 1M context and programmatic tool calling as its siblings: GPT-5.6 Luna — A core design strength of GPT-5.6 Luna.
Lowest cost at scale: GPT-5.6 Luna — At $1/$6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-5.6 Luna — At $1/$6 per 1M tokens it undercuts Claude Fable 5, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is the hardest reasoning and most complex problems: Claude Fable 5 — It is specifically built for that.
Anyone whose priority is cheapest gpt-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — That is its strongest area.
Claude Fable 5: where it fits
Anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive. Released June 9, 2026 by Anthropic, it is built for the hardest reasoning and most complex problems, long-horizon, multi-step agentic work, frontier-level analysis and research, and work where maximum capability outweighs cost.
Its trade-offs are real: highest price in the Claude lineup, and tier access was temporarily suspended in June 2026 under a US export-control directive. At $10 in / $50 out per million tokens, it sits in the premium price band.
GPT-5.6 Luna: where it fits
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Released July 9, 2026 by OpenAI, it is built for cheapest GPT-5.6 tier for high-volume drafting and automation, fast, affordable execution while keeping respectable coding, same 1M context and programmatic tool calling as its siblings, and high-throughput simple agentic jobs.
Its trade-offs: weak long-context recall deep in its 1M window (MRCR far below Sol), and lowest raw capability of the three GPT-5.6 tiers; no open weights. At $1 in / $6 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Claude Fable 5 and GPT-5.6 Luna overlap enough that the right pick depends on your specific job. GPT-5.6 Luna costs less per token; and each leads in its own area — Claude Fable 5 for the hardest reasoning and most complex problems, GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Claude Fable 5 or GPT-5.6 Luna better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Claude Fable 5 leans toward the hardest reasoning and most complex problems while GPT-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Fable 5 or GPT-5.6 Luna?
GPT-5.6 Luna is cheaper — $10/$50 per 1M tokens vs $1/$6 per 1M tokens, roughly 10× apart on input.
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Claude Fable 5 and GPT-5.6 Luna together?
Yes — a multi-model platform like LumiChats gives you Claude Fable 5, GPT-5.6 Luna and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Claude Fable 5 or GPT-5.6 Luna?
GPT-5.6 Luna — released July 9, 2026, about 30 days after Claude Fable 5.
Claude Fable 5 vs GPT-5.6 Luna
Anthropic · US | OpenAI · US · Updated June 2026
Quick verdict
Pick Claude Fable 5 for the hardest reasoning and most complex problems or long-horizon, multi-step agentic work. Pick GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation or fast, affordable execution while keeping respectable coding. On a tight budget at scale, GPT-5.6 Luna is the value pick.
Claude Fable 5 (Anthropic) and GPT-5.6 Luna (OpenAI) are two of the models people most often weigh against each other in 2026. Claude Fable 5 is anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive. GPT-5.6 Luna is the budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Price: GPT-5.6 Luna is about 10× cheaper on input ($1/$6 per 1M tokens vs $10/$50 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: GPT-5.6 Luna is the newer model by about 30 days (released July 9, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Claude Fable 5
GPT-5.6 Luna
Provider
Anthropic (US)
OpenAI (US)
Released
June 9, 2026
July 9, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$10/$50 per 1M tokens
$1/$6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
The hardest reasoning and most complex problems
Claude Fable 5
A core design strength of Claude Fable 5.
Long-horizon, multi-step agentic work
Claude Fable 5
A core design strength of Claude Fable 5.
Frontier-level analysis and research
Claude Fable 5
A core design strength of Claude Fable 5.
Cheapest GPT-5.6 tier for high-volume drafting and automation
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Fast, affordable execution while keeping respectable coding
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Same 1M context and programmatic tool calling as its siblings
GPT-5.6 Luna
A core design strength of GPT-5.6 Luna.
Lowest cost at scale
GPT-5.6 Luna
At $1/$6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-5.6 Luna
At $1/$6 per 1M tokens it undercuts Claude Fable 5, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is the hardest reasoning and most complex problems
→ Claude Fable 5
It is specifically built for that.
Anyone whose priority is cheapest gpt-5.6 tier for high-volume drafting and automation
→ GPT-5.6 Luna
That is its strongest area.
Claude Fable 5: where it fits
Anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive. Released June 9, 2026 by Anthropic, it is built for the hardest reasoning and most complex problems, long-horizon, multi-step agentic work, frontier-level analysis and research, and work where maximum capability outweighs cost.
Its trade-offs are real: highest price in the Claude lineup, and tier access was temporarily suspended in June 2026 under a US export-control directive. At $10 in / $50 out per million tokens, it sits in the premium price band.
GPT-5.6 Luna: where it fits
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Released July 9, 2026 by OpenAI, it is built for cheapest GPT-5.6 tier for high-volume drafting and automation, fast, affordable execution while keeping respectable coding, same 1M context and programmatic tool calling as its siblings, and high-throughput simple agentic jobs.
Its trade-offs: weak long-context recall deep in its 1M window (MRCR far below Sol), and lowest raw capability of the three GPT-5.6 tiers; no open weights. At $1 in / $6 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Claude Fable 5 and GPT-5.6 Luna overlap enough that the right pick depends on your specific job. GPT-5.6 Luna costs less per token; and each leads in its own area — Claude Fable 5 for the hardest reasoning and most complex problems, GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Claude Fable 5 and GPT-5.6 Luna without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
Is Claude Fable 5 or GPT-5.6 Luna better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Claude Fable 5 leans toward the hardest reasoning and most complex problems while GPT-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Fable 5 or GPT-5.6 Luna?
GPT-5.6 Luna is cheaper — $10/$50 per 1M tokens vs $1/$6 per 1M tokens, roughly 10× apart on input.
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Claude Fable 5 and GPT-5.6 Luna together?
Yes — a multi-model platform like LumiChats gives you Claude Fable 5, GPT-5.6 Luna and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Claude Fable 5 or GPT-5.6 Luna?
GPT-5.6 Luna — released July 9, 2026, about 30 days after Claude Fable 5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.