MoonshotAI

K2-Vendor-Verifier

Python2025–2026

MoonshotAI / K2-Vendor-Verifier

K2-Vendor-Verifier

Verify Precision of all Kimi K2 API Vendor

Explore on GitHub Read Hacker News discussions

10Distinct people

10Mentions

0Explicit recommenders

601GitHub stars

REPOSITORY AT A GLANCE

What to know before exploring

What it is

Verify Precision of all Kimi K2 API Vendor

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

moonshotai/kimi-vendor-verifier · linked in 2 of the same discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month10 dated mentions

Observed mentions: 2025-09-25 09:17:47 UTC to 2026-06-17 12:36:35 UTC.

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges

UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
Period	Start (UTC)	End (exclusive, UTC)	Mentions	Submissions	Comments
Sep 2025	2025-09-01 00:00:00 UTC	2025-10-01 00:00:00 UTC	2	1	1
Oct 2025	2025-10-01 00:00:00 UTC	2025-11-01 00:00:00 UTC	1	0	1
Nov 2025	2025-11-01 00:00:00 UTC	2025-12-01 00:00:00 UTC	2	0	2
Dec 2025	2025-12-01 00:00:00 UTC	2026-01-01 00:00:00 UTC	0	0	0
Jan 2026	2026-01-01 00:00:00 UTC	2026-02-01 00:00:00 UTC	1	0	1
Feb 2026	2026-02-01 00:00:00 UTC	2026-03-01 00:00:00 UTC	0	0	0
Mar 2026	2026-03-01 00:00:00 UTC	2026-04-01 00:00:00 UTC	0	0	0
Apr 2026	2026-04-01 00:00:00 UTC	2026-05-01 00:00:00 UTC	1	0	1
May 2026	2026-05-01 00:00:00 UTC	2026-06-01 00:00:00 UTC	0	0	0
Jun 2026	2026-06-01 00:00:00 UTC	2026-07-01 00:00:00 UTC	3	0	3

What Hacker News says

10 sources

thehamkercat·Jun 17, 2026

Kimi K2 had a vendor verifier: https://github.com/MoonshotAI/K2-Vendor-Verifier (there's a table which shows comparison between vendors) Also, it seems there's a general one as well (for all kimi models?): https://github.com/MoonshotAI/Kimi-Vendor-Verifier

In GLM-5.2 is the new leading open weights model on Artificial Analysis

jc4p·Jun 4, 2026

Sorry I don't understand, you're saying the direct providers aren't the canonical source you'd recommend? If I was running these on my own machine or GPU wouldn't the argument then be "Well you didn't use the real providers?" For the record I started doing this approach because the Kimi team released this which was shocking to me: https://github.com/MoonshotAI/K2-Vendor-Verifier

In I built a vulnerable app and spent $1,500 seeing if LLMs could hack it

mdp2021·Jun 3, 2026

> [Groq] rounded out the bottom of Kimi's verification program Ok, this is interesting: https://github.com/MoonshotAI/K2-Vendor-Verifier/ > Did you do any research yourself? How, systematically speaking? I would need a properly structured embeddings DB over HN (and possibly a few other sources). I am not aware of any satisfactory (reliable) RAG available. I have found this: https://hackersearch.net which seems to be off at the moment. So, when John says "Jake I experienced as so itchy", I may expect some sauce from the speaker, not the tiniest crystal of the juice, if my takeaway is not just to be "John had a suboptimal experience with Jake". (And itchingly, "What's "itchy"?" ("what "random errors"?", "what "silly quirks"?")).

In How is Groq raising more money?

jychang·Apr 21, 2026

It's old, Kimi's been doing this for months now. https://github.com/MoonshotAI/K2-Vendor-Verifier https://github.com/MoonshotAI/Kimi-Vendor-Verifier Note, this is before K2.5 and K2.6 even launched.

In Kimi vendor verifier – verify accuracy of inference providers

Topfi·Jan 29, 2026

Very impressive, would love to see the results from the verifier for this fully local setup: https://github.com/MoonshotAI/K2-Vendor-Verifier

In Kimi K2.5 on 2 Mac Studios (<$20K) running at 24 TPS

msp26·Nov 8, 2025

Groq does quantise. Look at this benchmark from moonshotai for K2 where they compare their official implementation to third party providers. https://github.com/MoonshotAI/K2-Vendor-Verifier It's one of the lowest rated on that table.

In Cerebras Code now supports GLM 4.6 at 1000 tokens/sec

Palmik·Nov 7, 2025

This is most likely issue on the side of the inference provider: https://github.com/MoonshotAI/K2-Vendor-Verifier For example, Together AI has only 71% success rate, while the official API has 100% success rate.

In Kimi K2 Thinking, a SOTA open-source trillion-parameter reasoning model

wishawa·Oct 12, 2025

Inference is impressively fast. But what about quality? In the Kimi vendor verifier (https://github.com/MoonshotAI/K2-Vendor-Verifier/), Together has one of the highest tool call failure rates (>300 failures over the benchmark, compared to 0-2 for the official API, groq, SiliconFlow, and Infinigence).

In AdapTive-LeArning Speculator System (ATLAS): Faster LLM inference

vitorgrs·Sep 30, 2025

GLM 4.5 for me one of the best coding model when running with agents such as Claude Code and Opencode (excluding Claude and GPT-5). Looking forward to try GLM 4.6. But Z AI should do like KIMI¹ and launch a verifier to see how GLM models behave on 3rd party providers. [1] https://github.com/MoonshotAI/K2-Vendor-Verfier

In GLM-4.6: Advanced Agentic, Reasoning and Coding Capabilies

xxr3376·Sep 25, 2025Submission

K2VV: Wild Precision Gaps Across "Kimi K2" API Vendors

4 points · Open discussion