Pick Claude Fable 5.1 for terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%) or cursorbench 3.2 agentic coding (73.4%). Pick GPT-6 Sol for openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment or openai says it makes about half as many mistakes as gpt-5.6 sol. On a tight budget at scale, GPT-6 Sol is the value pick.
Claude Fable 5.1 (Anthropic) and GPT-6 Sol (OpenAI) are two of the models people most often weigh against each other in 2026. Claude Fable 5.1 is anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores. GPT-6 Sol is openAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: GPT-6 Sol is about 5× cheaper on input ($2/$10 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: 1M tokens vs 1.05M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: GPT-6 Sol is the newer model by about 21 days (released September 22, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Claude Fable 5.1
GPT-6 Sol
Provider
Anthropic (US)
OpenAI (US)
Released
September 1, 2026
September 22, 2026
Context window
1M tokens (~1,500 pages)
1.05M tokens (~1,575 pages)
Price (in/out)
$10/$50 per 1M tokens
$2/$10 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text, image
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%): Claude Fable 5.1 — Claude Fable 5.1 lists terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%) among its strengths; GPT-6 Sol does not.
CursorBench 3.2 agentic coding (73.4%): Claude Fable 5.1 — Claude Fable 5.1 lists cursorBench 3.2 agentic coding (73.4%) among its strengths; GPT-6 Sol does not.
Cache-read pricing cut to a quarter of other Claude models: Claude Fable 5.1 — GPT-6 Sol is comparatively weak here — cache-read pricing ($0.20/MTok) still costlier than Luna's ($0.01/MTok) for high-cache workloads
OpenAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment: GPT-6 Sol — OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it runs cheaper at $2/$10 per 1M tokens.
OpenAI says it makes about half as many mistakes as GPT-5.6 Sol: GPT-6 Sol — OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it is the newer of the two.
Priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30): GPT-6 Sol — At $2/$10 per 1M tokens it undercuts Claude Fable 5.1 ($10/$50 per 1M tokens), and that gap compounds at volume.
Lowest cost at scale: GPT-6 Sol — At $2/$10 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-6 Sol — At $2/$10 per 1M tokens it undercuts Claude Fable 5.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-6 Sol — Larger 1.05M tokens window fits more in one prompt.
Anyone whose priority is terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%): Claude Fable 5.1 — It is specifically built for that.
Anyone whose priority is openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment: GPT-6 Sol — That is its strongest area.
Claude Fable 5.1: where it fits
Anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores. Released September 1, 2026 by Anthropic, it is built for terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%), cursorBench 3.2 agentic coding (73.4%), cache-read pricing cut to a quarter of other Claude models, and long, multistep, document-heavy professional work with 1M-token context.
Its trade-offs are real: anthropic has not published an official SWE-bench Verified score for this model, restricted Mythos 5.1 variant outscores it on some benchmarks due to lighter safeguards (Terminal-Bench 4.0: 60.9% vs 55.8%), and closed weights, no self-hosting option. At $10 in / $50 out per million tokens, it sits in the premium price band.
GPT-6 Sol: where it fits
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. Released September 22, 2026 by OpenAI, it is built for openAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment, openAI says it makes about half as many mistakes as GPT-5.6 Sol, priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30), and 1.05M-token context window, input capped at 922K.
Its trade-offs: more reasoning capability than sibling GPT-6 Luna, but still positioned below flagship GPT-6 Astra, and cache-read pricing ($0.20/MTok) still costlier than Luna's ($0.01/MTok) for high-cache workloads. At $2 in / $10 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Claude Fable 5.1 and GPT-6 Sol overlap enough that the right pick depends on your specific job. GPT-6 Sol costs less per token; GPT-6 Sol holds the larger context; and each leads in its own area — Claude Fable 5.1 for terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%), GPT-6 Sol for openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Claude Fable 5.1 or GPT-6 Sol 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 5.1 leans toward terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%) while GPT-6 Sol leans toward openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Fable 5.1 or GPT-6 Sol?
GPT-6 Sol is cheaper — $10/$50 per 1M tokens vs $2/$10 per 1M tokens, roughly 5× apart on input.
Which has the bigger context window?
Effectively neither — 1M tokens vs 1.05M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Claude Fable 5.1 and GPT-6 Sol together?
Yes — a multi-model platform like LumiChats gives you Claude Fable 5.1, GPT-6 Sol 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 5.1 or GPT-6 Sol?
GPT-6 Sol — released September 22, 2026, about 21 days after Claude Fable 5.1.
Claude Fable 5.1 vs GPT-6 Sol
Anthropic · US | OpenAI · US · Updated June 2026
Quick verdict
Pick Claude Fable 5.1 for terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%) or cursorbench 3.2 agentic coding (73.4%). Pick GPT-6 Sol for openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment or openai says it makes about half as many mistakes as gpt-5.6 sol. On a tight budget at scale, GPT-6 Sol is the value pick.
Claude Fable 5.1 (Anthropic) and GPT-6 Sol (OpenAI) are two of the models people most often weigh against each other in 2026. Claude Fable 5.1 is anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores. GPT-6 Sol is openAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GPT-6 Sol is about 5× cheaper on input ($2/$10 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: 1M tokens vs 1.05M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: GPT-6 Sol is the newer model by about 21 days (released September 22, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Claude Fable 5.1
GPT-6 Sol
Provider
Anthropic (US)
OpenAI (US)
Released
September 1, 2026
September 22, 2026
Context window
1M tokens (~1,500 pages)
1.05M tokens (~1,575 pages)
Price (in/out)
$10/$50 per 1M tokens
$2/$10 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image
text, image
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%)
Claude Fable 5.1
Claude Fable 5.1 lists terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%) among its strengths; GPT-6 Sol does not.
CursorBench 3.2 agentic coding (73.4%)
Claude Fable 5.1
Claude Fable 5.1 lists cursorBench 3.2 agentic coding (73.4%) among its strengths; GPT-6 Sol does not.
Cache-read pricing cut to a quarter of other Claude models
Claude Fable 5.1
GPT-6 Sol is comparatively weak here — cache-read pricing ($0.20/MTok) still costlier than Luna's ($0.01/MTok) for high-cache workloads
OpenAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment
GPT-6 Sol
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it runs cheaper at $2/$10 per 1M tokens.
OpenAI says it makes about half as many mistakes as GPT-5.6 Sol
GPT-6 Sol
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens — and it is the newer of the two.
Priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30)
GPT-6 Sol
At $2/$10 per 1M tokens it undercuts Claude Fable 5.1 ($10/$50 per 1M tokens), and that gap compounds at volume.
Lowest cost at scale
GPT-6 Sol
At $2/$10 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-6 Sol
At $2/$10 per 1M tokens it undercuts Claude Fable 5.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-6 Sol
Larger 1.05M tokens window fits more in one prompt.
Anyone whose priority is terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%)
→ Claude Fable 5.1
It is specifically built for that.
Anyone whose priority is openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment
→ GPT-6 Sol
That is its strongest area.
Claude Fable 5.1: where it fits
Anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores. Released September 1, 2026 by Anthropic, it is built for terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%), cursorBench 3.2 agentic coding (73.4%), cache-read pricing cut to a quarter of other Claude models, and long, multistep, document-heavy professional work with 1M-token context.
Its trade-offs are real: anthropic has not published an official SWE-bench Verified score for this model, restricted Mythos 5.1 variant outscores it on some benchmarks due to lighter safeguards (Terminal-Bench 4.0: 60.9% vs 55.8%), and closed weights, no self-hosting option. At $10 in / $50 out per million tokens, it sits in the premium price band.
GPT-6 Sol: where it fits
OpenAI's September 22, 2026 mid-tier update — Astra-derived improvements at half the GPT-5.6 Sol price, $2/$10 per million tokens. Released September 22, 2026 by OpenAI, it is built for openAI's everyday-work tier below GPT-6 Astra, built with the same methods that improved Astra's professional work, factuality, coding, computer use, and alignment, openAI says it makes about half as many mistakes as GPT-5.6 Sol, priced at half of the GPT-5.6 Sol/Luna generation's rates ($2/$10 vs GPT-5.6 Sol's $5/$30), and 1.05M-token context window, input capped at 922K.
Its trade-offs: more reasoning capability than sibling GPT-6 Luna, but still positioned below flagship GPT-6 Astra, and cache-read pricing ($0.20/MTok) still costlier than Luna's ($0.01/MTok) for high-cache workloads. At $2 in / $10 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Claude Fable 5.1 and GPT-6 Sol overlap enough that the right pick depends on your specific job. GPT-6 Sol costs less per token; GPT-6 Sol holds the larger context; and each leads in its own area — Claude Fable 5.1 for terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%), GPT-6 Sol for openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Claude Fable 5.1 and GPT-6 Sol 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 5.1 or GPT-6 Sol 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 5.1 leans toward terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%) while GPT-6 Sol leans toward openai's everyday-work tier below gpt-6 astra, built with the same methods that improved astra's professional work, factuality, coding, computer use, and alignment, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Fable 5.1 or GPT-6 Sol?
GPT-6 Sol is cheaper — $10/$50 per 1M tokens vs $2/$10 per 1M tokens, roughly 5× apart on input.
Which has the bigger context window?
Effectively neither — 1M tokens vs 1.05M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Claude Fable 5.1 and GPT-6 Sol together?
Yes — a multi-model platform like LumiChats gives you Claude Fable 5.1, GPT-6 Sol 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 5.1 or GPT-6 Sol?
GPT-6 Sol — released September 22, 2026, about 21 days after Claude Fable 5.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.