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
Day 7Launch day vs. day 7
AI launches, checked against real usersLast re-stamped 30 Oct 2026

AI models / Compare

Claude Opus 5.5 vs EmbeddingGemma 2: which delivered after 7 days?

EmbeddingGemma 2 got the stronger stamp (Delivered) against Claude Opus 5.5 (Partly), based on the user reports linked on each receipt.

Claude Opus 5.5EmbeddingGemma 2
VerdictPartlyDelivered
Claims held04
Claims mixed31
Claims failed00
Claims unclear20
User reports714
Launched22 Sept 20266 Oct 2026
Last stamped22 Oct 202625 Oct 2026

No. 002 · Anthropic

Claude Opus 5.5

PartlyDay 7 verdict

The lower list price is real, but users report limits draining faster, more thinking tokens and safeguard false alarms, and nobody has independently confirmed the 40% saving.

Launched
22 Sept 2026
Stamped
22 Oct 2026
Claims
✓0 held · ~3 mixed · ✗0 failed · ?2 unclear
Reports
7 (1 praise · 6 problem · 0 mixed)

What they claimed

“It performs at the level of Claude Fable 5.1 on most work and costs 40% less to run than Opus 5.”
~ Mixed
“Input and output tokens are $4 and $20 per million, 20% less than Opus 5.”
? Unclear
“In addition to the price drop, we’re increasing five-hour usage limits on Pro, Max, Team, and seat-based Enterprise plans.”
~ Mixed
“It is much less likely than recent models to take hard-to-reverse actions or act outside the boundaries it’s been given”
~ Mixed
“Opus 5.5 also generates output more than 30% faster than Opus 5.”
? Unclear

Full receipt

No. 009 · Google

EmbeddingGemma 2

DeliveredDay 7 verdict

The open weights, the shared text-image-audio space and the code gains check out in independent tests; text-only users get no boost, as Google said.

Launched
6 Oct 2026
Stamped
25 Oct 2026
Claims
✓4 held · ~1 mixed · ✗0 failed · ?0 unclear
Reports
14 (6 praise · 5 problem · 3 mixed)

What they claimed

“Today, we’re launching EmbeddingGemma 2, expanding beyond text to unify code, images, video, and audio in a shared embedding space.”
✓ Holds
“Built on the Gemma 4 architecture and released under a commercially permissive Apache 2.0 license, EmbeddingGemma 2 has 740 million parameters, making it optimal for on-device inference.”
✓ Holds
“Using Matryoshka Representation Learning (MRL), developers can dynamically truncate output vectors from 768 dimensions down to 512, 256, or 128 dimensions.”
✓ Holds
“EmbeddingGemma 2 matches the strong multilingual text performance of EmbeddingGemma while delivering a significant 9.92-point improvement on code performance (in MTEB Code, from 68.76 to 78.68), making it well-suited for local codebase indexing, semantic code search, and coding agent retrieval.”
✓ Holds
“We worked closely with the following partners to ensure EmbeddingGemma 2 works immediately where you build:”
~ Mixed

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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