Day 7 · 2026-10-30
15 launches checked60 claims quoted word for word87 user reports linked10 verified fixes linked6 corrections publishedLive 7 days5 of 5 founding sponsor spots left
AI launches, checked against real usersLast re-stamped 30 Oct 2026

AI models / Compare

GPT-6.1 Sol vs LFM3: which delivered after 7 days?

GPT-6.1 Sol is stamped Partly; LFM3 is still Too early to call, so this comparison isn't settled yet.

GPT-6.1 SolLFM3
VerdictPartlyToo early
Claims held00
Claims mixed30
Claims failed00
Claims unclear23
User reports52
Launched29 Sept 202627 Oct 2026
Last stamped22 Oct 202629 Oct 2026

No. 004 · OpenAI

GPT-6.1 Sol

PartlyDay 7 verdict

It arrived and Ultrafast followed, but 'available today' took app updates for many users, Ultrafast is limited to top plans, and some users report over-refusals.

Launched
29 Sept 2026
Stamped
22 Oct 2026
Claims
✓0 held · ~3 mixed · ✗0 failed · ?2 unclear
Reports
5 (0 praise · 3 problem · 2 mixed)

What they claimed

“GPT-6.1 Sol is available starting today to all Plus, Pro, Business, Enterprise, and Edu users in ChatGPT Work and Codex.”
~ Mixed
“In the coming days, we’ll also offer GPT-6.1 Sol Ultrafast, with up to 8x faster token generation compared to its standard speed in Codex.”
~ Mixed
“GPT-6.1 Sol is more transparent about its limitations and more reliable at respecting user intent and safety constraints.”
~ Mixed
“We’re introducing GPT-6.1 Sol, an upgrade to GPT-6 Sol that nearly matches GPT-6 Astra’s intelligence on agentic coding, computer use, and professional work at one-fifth of Astra’s standard input and output token prices.”
? Unclear
“Its standard API prices are $2 per million input tokens, $0.10 per million cached input tokens, and $10 per million output tokens.”
? Unclear

Full receipt

No. 013 · Liquid AI

LFM3

Day 3 of 7
Too earlyDay 7 verdict

Two days in, only a few first-hand comments exist, and one reports a load failure and a wrong answer.

Launched
27 Oct 2026
Stamped
29 Oct 2026
Claims
✓0 held · ~0 mixed · ✗0 failed · ?3 unclear
Reports
2 (0 praise · 1 problem · 1 mixed)

What they claimed

“a new tri-hybrid architecture and training recipe allow LFM3-1.7B to outperform our previous LFM2.5-2.6B while using 35% fewer parameters.”
? Unclear
“the text model fits in about 1 GB at 4-bit precision.”
? Unclear
“256K context window for the text model.”
? Unclear

Full receipt

Both stamps come from the public user reports linked on each receipt, under the same method. Verdicts are opinion and are never paid for.

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