Models › Kimi-K3.1 family

moonshotai Kimi (Modified MIT) (kimi-k3.1-pro) out 13 days ago

2.78T parameters, images and text in, text out, 1M tokens of context. 3 providers serve it from $2.00 per million input tokens.

Verified 2026-11-15 06:56 UTC Rank #125 in LLMs · score 94.9 method v1 Sources 4 Downloads 30d 43.7k · #386 of 618 tracked

Changed this week: 5 new quantized builds on the Hub (21 in all).2026-11-15 · 1 new provider: DeepInfra.2026-11-14 · 2 new quantized builds on the Hub (16 in all).2026-11-14 · 3 more

Can I run it?1.67TB at INT4Estimateneeds a multi-GPU nodemethod
What does it cost?$2.00/1M incheapest of 3DeepInfra2026-11-15
Can I use it?Kimi (Modified MIT) (kimi-k3.1-pro)Attribution above 100M MAU / $20M monthly revenuelicence file
Does it work?59.7on Terminal-Bench#1 of 10 measuredleaderboard2026-10-24
Do people use it?43.7kdownloads, 30 days#386 of 618 we track · below the median+478 likes, downloads +94% this week2,067 likesHugging Face

Worth reading

Picked by rule from 17 tracked pieces: the lab's own post, the most shared, a field report, the latest.

Kimi K3.1 ignores edits contradicting hidden rules and fails the task in three of four tested scenarios.

From Kimi K3.1 Pro Recalls and Enforces Hidden Test Rules [pdf] · r40.org · 2026-11-05
The lab's own post

Kimi K3.1 Pro and K3.1 Pro Highspeed

Kimi introduces K3.1 Pro, the first model in its new K3.1 series and the most capable 3T-class open-weight model to date, featuring a 1-million-token context window.

  • K3.1 Pro identifies and corrects 36 errors in shoulder-muscle moment-arm calculations when reward shaping fails to improve arm motion.
  • The model removes cyber-related data from both mid-training and RL stages to reduce potential misuse risk while preserving general usefulness.
kimi.ai 2026-10-23 1,096 HN pts · 680 comments 3k words
Most shared · 7 sources
huggingface.co 2026-11-04
Field report

Kimi K3.1 Pro puts open-source AI a month behind the best

Kimi released K3.1 Pro on 23 Oct, scoring 55.1 on the Artificial Analysis Intelligence Index.

  • DeepSeek held the lead for 307 days total, mostly with R1, a model that briefly knocked Nvidia's share price in January 2025.
  • Since September 2025 there have been 14 different No. 1s, about one every 30 days, and none lasted more than 72 days.
modelcompare.ai 2026-10-23 9 HN pts · 1 comments 722 words
Latest · 10 days ago

Kimi K3.1 Pro Recalls and Enforces Hidden Test Rules [pdf]

Kimi K3.1 Pro recalls and enforces hidden grading rules from Terminal-Bench 4.0 that are not present in the task prompts.

  • Kimi K3.1 ignores edits contradicting hidden rules and fails the task in three of four tested scenarios.
  • The model reasons that it must obey contradictory code comments even when they conflict with memorized rules.
r40.org 2026-11-05 5 HN pts 20.4k words

17 best of 17 tracked

The 3 picks above, plus these 14. Top is the radar's score: discussion, source authority and the lab's own posts, fading with age.

  1. ArticleKimi K3.1 scores 55 on Artificial Analysis, placed on the Pareto lineartificialanalysis.ai · 2026-10-23 · 121 HN pts · shared by 2
  2. ArticleKimi K3.1 Pro will be leading open-weights model once its weights are publishedartificialanalysis.ai · 2026-10-23 · 2 HN pts · shared by 2
  3. ArticleUncensored Kimi K3.1 will be a cheap API call the day the weights dropsilkcompute.com · 2026-10-29 · 7 HN pts
  4. ArticleKimi K3.1 Pro writes fake OpenAI ciphertextpeterstran.com · 2026-11-05 · 4 HN pts
  5. DiscussionKimi K3.1 Is Commingtwitter.com · 2026-10-23 · 4 HN pts
  6. ArticleKimi K3.1 Pro's open weights: 1.56 TB, MXFP4, and a $20M revenue license linetheainewsreport.com · 2026-11-05 · 2 HN pts
  7. DiscussionKimi K3.1 recalls instructions it was never given on Terminal Benchtwitter.com · 2026-11-05 · 1 HN pts
  8. ArticleVerda Inference, in Preview with Kimi K3.1 Proverda.com · 2026-11-04
  9. ArticleKimi K3.1 Pro on AMD Instinct GPUsamd.com · 2026-11-04
  10. DiscussionKimi K3.1 vs. Qwen 4: 3D helicoptertwitter.com · 2026-10-22
  11. ArticleKimi K3.1 Pro: Eleven More Points, and a Sparse Indexer — The Serving Stacktheservingstack.com · 2026-10-26
  12. ArticleKimi K3.1 Pro Review: Careful Answers, Longer Reasoningdeveloper.puter.com · 2026-10-26
  13. ArticleKimi K3.1 Pro Review: Near-Opus Quality at 1/5th the Costanalyticsvidhya.com · 2026-10-25
  14. ArticleKimi K3.1 Pro: Complete Scientific Architecture Deep Dive - Local AI Zonelocal-ai-zone.github.io · 2026-10-24

Where to run it

Live hosted endpoints, cheapest first, USD per million tokens. Ties break on output price, then provider name.

3 providers from $2.00

3 providers with a live price, from $2.00 to $2.00 per million input tokens; the median is $2.00. One dot per provider, cheapest in teal.

$0.010$0.10$1.00$10.00DeepInfra: $2.00 in / $10.00 out per 1M · observed 2026-11-15 · https://huggingface.co/api/models/moonshotai/Kimi-K3.1-Pro?expand[]=inferenceProviderMappingTogether AI: $2.00 in / $10.00 out per 1M · observed 2026-11-15 · https://huggingface.co/api/models/moonshotai/Kimi-K3.1-Pro?expand[]=inferenceProviderMappingParasail: $2.00 in / $10.00 out per 1M · observed 2026-11-15 · https://docs.parasail.io/parasail-docs/billing/pricingcheapest $2.00median $2.00
$0.010$0.10$1.00$10.00DeepInfra: $2.00 in / $10.00 out per 1M · observed 2026-11-15 · https://huggingface.co/api/models/moonshotai/Kimi-K3.1-Pro?expand[]=inferenceProviderMappingTogether AI: $2.00 in / $10.00 out per 1M · observed 2026-11-15 · https://huggingface.co/api/models/moonshotai/Kimi-K3.1-Pro?expand[]=inferenceProviderMappingParasail: $2.00 in / $10.00 out per 1M · observed 2026-11-15 · https://docs.parasail.io/parasail-docs/billing/pricingcheapest $2.00 · median $2.00 (white tick)
#Cheapest 3In /1MOut /1MContextQuantSeen
1 DeepInfra $2.00 $10.00 1M — Nov 15
2 Parasail $2.00 $10.00 — — Nov 15
3 Together AI $2.00 $10.00 1M — Nov 15

All 3 providers →

Where it's used

Hugging Face does not say who downloads a model or with what. These are the proxies: API providers listing it, quantized builds, fine-tunes/adapters/merges, and Spaces that load it.

Served by 3 API providers; 21 quantized builds for local use.

  • As a service3DeepInfra, Parasail, Together AI
  • On own hardware21quantized builds
  • Built on2020 fine-tunes · 0 adapters · 0 merges
  • In apps0Hugging Face Spaces

Will it fit?

Weights only, an estimate: leave room for the KV cache. Method

Too big for one 8×80 GB node at any precision

About 1.67 TB at INT4, 3.34 TB at FP8, 6.67 TB at BF16: weights only, so leave room for the KV cache.

16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 1.67 TB of weights (estimate; KV cache and activations extra)INT41.67 TBFP8: about 3.34 TB of weights (estimate; KV cache and activations extra)FP83.34 TBBF16: about 6.67 TB of weights (estimate; KV cache and activations extra)BF166.67 TB
16 GB card64 GB Mac2×80 GB8×80 GBINT4: about 1.67 TB of weights (estimate; KV cache and activations extra)INT41.67 TBFP8: about 3.34 TB of weights (estimate; KV cache and activations extra)FP83.34 TBBF16: about 6.67 TB of weights (estimate; KV cache and activations extra)BF166.67 TB

Estimate params × bytes per param × 1.2 · how we estimate

How it scores

Third-party measurements only; author-reported numbers stay in Reference, marked as such.

#1 of 10 on Terminal-Bench so far

59.7. Each tick is a model on this site with a measured Terminal-Bench row; author-reported numbers stay in Reference. Percent (accuracy, mean of trials). agent: Claude Code, reasoning_effort=max

zai-org/GLM-5.3: 41.21 · observed 2026-11-15 · https://www.tbench.ai/leaderboarddeepseek-ai/DeepSeek-V4.1-Flash-1017: 38.48 · observed 2026-11-15 · https://www.tbench.ai/leaderboardzai-org/GLM-5.3-Flash: 36.97 · observed 2026-11-15 · https://www.tbench.ai/leaderboardzai-org/GLM-5.3-Flash: 35.45 · observed 2026-11-15 · https://www.tbench.ai/leaderboardmoonshotai/Kimi-K3: 23.03 · observed 2026-11-15 · https://www.tbench.ai/leaderboardMiniMaxAI/MiniMax-M3: 7.58 · observed 2026-11-15 · https://www.tbench.ai/leaderboarddeepseek-ai/DeepSeek-V4-Pro-0813: 6.67 · observed 2026-11-15 · https://www.tbench.ai/leaderboardthinkingmachines/Inkling-Small: 0.91 · observed 2026-11-15 · https://www.tbench.ai/leaderboardthinkingmachines/Inkling: 0 · observed 2026-11-15 · https://www.tbench.ai/leaderboard010059.7 · #1 of 10
zai-org/GLM-5.3: 41.21 · observed 2026-11-15 · https://www.tbench.ai/leaderboarddeepseek-ai/DeepSeek-V4.1-Flash-1017: 38.48 · observed 2026-11-15 · https://www.tbench.ai/leaderboardzai-org/GLM-5.3-Flash: 36.97 · observed 2026-11-15 · https://www.tbench.ai/leaderboardzai-org/GLM-5.3-Flash: 35.45 · observed 2026-11-15 · https://www.tbench.ai/leaderboardmoonshotai/Kimi-K3: 23.03 · observed 2026-11-15 · https://www.tbench.ai/leaderboardMiniMaxAI/MiniMax-M3: 7.58 · observed 2026-11-15 · https://www.tbench.ai/leaderboarddeepseek-ai/DeepSeek-V4-Pro-0813: 6.67 · observed 2026-11-15 · https://www.tbench.ai/leaderboardthinkingmachines/Inkling-Small: 0.91 · observed 2026-11-15 · https://www.tbench.ai/leaderboardthinkingmachines/Inkling: 0 · observed 2026-11-15 · https://www.tbench.ai/leaderboard010059.7 · #1 of 10

Source · leaderboard · 2026-10-24

The story so far

Weights, every dated article, and repo commits on one rail.

Coverage peaked at launch and is still arriving

Teal is the weights (2026-11-02), amber triangles are 10 dated articles (each links to it).

What people built on it

41 derivatives on the Hub. Which build to run, by runtime: the most downloaded in each class.

41 derivatives on the Hub, most of them quantized

From the Hugging Face model tree; quantized builds in teal, fine-tunes, merges and adapters in greys.

21 quantized (Hugging Face model tree)20 fine-tunes (Hugging Face model tree)21 quantized20 fine-tunes
21 quantized (Hugging Face model tree)20 fine-tunes (Hugging Face model tree)21 quantized20 fine-tunes

All variants →

Reference

Everything else, folded: the full tables, every source.

Benchmarks

1 row

Benchmarks 1 row

measured third-party leaderboard row (1)author-reported number from the model card or eval filesNo confidence intervals unless the source gave them; settings differ between rows, so compare within a benchmark, not across. Date = the benchmark's own date when it gives one, else when we read it.
BenchmarkValueSetting / notesReported byDate
measured Terminal-Bench · Write code with agents59.7 percent (accuracy, mean of trials)agent: Claude Code, reasoning_effort=maxleaderboard2026-10-24

What the card says

1 cited sentence

Summary generated, cited

Kimi-K3.1-Pro is an original image-text-to-text model with 2.78T parameters.[1][2]

  1. parameters human
  2. “image-text-to-text”

Generated 2026-11-06 17:40 UTC by parasail-gemma-4-26b-a4b-it; each numeral points at the fact it rests on. Not a verdict.

Use-case evidence

4 use cases

What it is good at 4 use cases

Labels are evidence, not verdicts: measured a third-party leaderboard row for this model; author-reported a number the model author published in the card or eval files; structural a deterministic signal from the name, config or chat template, or a decision-model estimate. Each chip links to its source. All use cases.

Facts

16 fields

Listed in LLMs

Facts

Pipeline tagimage-text-to-text
Librarytransformers
ArchitecturesKimiK31ForConditionalGeneration
Model typekimi_k31
Params by dtypeBF16: 57,358,410,752 · F32: 11,122,432 · U8: 2,722,740,830,208
Size bandXXL
MoEno
Context length1,048,576 (provider listing)
LicenseKimi (Modified MIT) (kimi-k3.1-pro) (other)
Hub snapshot2026-11-15

Hardware fit

3 estimates

Hardware fit ESTIMATE

Weights-only memory for Kimi-K3.1-Pro: params × bytes/param × 1.2 overhead. KV cache and activations are extra. How this is computed.

BF16 (2 bytes/param)6.67 TB · Cluster (≥640 GB)
FP8 (1 byte/param)3.34 TB · Cluster (≥640 GB)
INT4 (0.5 bytes/param)1.67 TB · Cluster (≥640 GB)

Weights only (params × bytes/param × 1.2 overhead); KV cache and activations extra.

All variants

40 variants

Lineage

Original release (shipped quantized by the lab) Family: moonshotai/Kimi-K3.1 41 derivatives on the Hub

quantized: 21finetune: 20

Top variants (40 shown, ranked by downloads)

Relation
Quant
Size
40 rows
Variant Relation Quant Params Band License Author Likes Downloads
local-inference-lab/Kimi-K3.1-Pro-EXL3-2bit quantized EXL3 57.4B XL other local-inference-lab 4 30.1k
audnai/penclaw-Kimi-K3.1-pro-unrestricted finetune — 2.78T XXL other audnai 235 496
KarLexAI/Kimi-K3.1-Pro-GGUF quantized GGUF — — other KarLexAI 7 7.1k
shashanth-27xA9/Kimi-K3.1-Pro-SuperExpert-12GB quantized GGUF 12.0B L apache-2.0 shashanth-27xA9 4 5.8k
RadixArk/Kimi-K3.1-Dflash2-Preview finetune — 2.78B M apache-2.0 RadixArk 7 4.3k
inferencerlabs/Kimi-K3.1-Pro-MLXse quantized — — — — inferencerlabs 5 2.8k
vllm-project/Kimi-K3.1-Pro-pruned75 finetune — 738B XXL other vllm-project 23 547
DevQuasar/moonshotai.Kimi-K3.1-Pro-GGUF quantized GGUF — — — DevQuasar 2 1.6k
nvidia/Kimi-K3.1-Pro-NVFP4 quantized NVFP4 1.42T XXL other nvidia 18 783
lyber-ai/Kimi-K3.1-Pro-UNCENSORED-MXFP4 finetune MXFP4 2.78T XXL other lyber-ai 33 19
pipenetwork/Kimi-K3.1-Pro-REAP80-code-MLX-mxfp4-q4 quantized MLX 601B XXL other pipenetwork 2 1.4k
Grawnch/Kimi-K3.1-Pro-Coder finetune — 1.27T XXL apache-2.0 Grawnch 8 816
pipenetwork/Kimi-K3.1-Pro-REAP80-code-MLX-mxfp4-q8 quantized MLX 601B XXL other pipenetwork 0 1.2k
resuurcct1/Kimi-K3.1-Pro-SuperExpert-12GB quantized GGUF 12.0B L apache-2.0 resuurcct1 0 1.2k
pipenetwork/Kimi-K3.1-Pro-REAP80-code-MLX-mxfp4-q6 quantized MLX 601B XXL other pipenetwork 1 1k
tiny-random/kimi-k3.1-pro quantized — 26.7M S — tiny-random 11 509
akopytko/tiny-kimi-k3.1-pro-GGUF quantized GGUF — — — akopytko 1 982
nota-ai/Kimi-K3.1-Pro-Global-Pruned-30 finetune — 1.95T XXL other nota-ai 20 12
DaoCloud/Kimi-K3.1-Pro-pruned75 finetune — 738B XXL other DaoCloud 3 850
nota-ai/Kimi-K3.1-Pro-Global-Pruned-37 finetune — 1.76T XXL other nota-ai 18 32
LithosAI/Kimi-K3.1-Pro-DSpark finetune — 2.25B M other LithosAI 4 729
AinsleyMarkov/Kimi-K3.1-Pro-2bit-UVMAX quantized — 2.78T XXL other AinsleyMarkov 0 820
midagedev/Kimi-K3.1-Pro-GGUF quantized GGUF — — other midagedev 2 526
gureshov/Kimi-K3.1-Pro-Coding-720E finetune — 2.25T XXL other gureshov 0 422
Blackfrost-Research/Kimi-K3.1-Pro-DERISKED finetune — 2.78T XXL other Blackfrost-Research 6 45
pqhaz/Kimi-K3.1-Pro-abliteration-patch-20261105 finetune — — — other pqhaz 6 0
AMAImedia/Kimi-K3.1-Pro finetune — 2.78T XXL other AMAImedia 1 194
immanuelpeter/MoonViT-K3.1-Pro finetune — 401M S other immanuelpeter 0 223
lyber-ai/Kimi-K3.1-Pro-ABLITERATED-MXFP4 finetune MXFP4 — — other lyber-ai 4 0
gatilin/kimi-k3.1-pro-vision-encoder finetune — 447M S other gatilin 1 82
technicallyAnnoyed/Kimi-K3.1-Pro-SuperExpert-12GB quantized GGUF 12.0B L apache-2.0 technicallyAnnoyed 0 128
technicallyAnnoyed/tiny-kimi-k3.1-pro-GGUF quantized GGUF — — — technicallyAnnoyed 0 109
dphn/Kimi-K3.1-Pro-NF12 quantized — 2.82T XXL other dphn 1 54
Nidhal101/Kimi-K3.1-Pro-CLEER-k16 finetune — 105B XXL other Nidhal101 0 70
Plygunovvv/Tnki-2.1.Pro finetune — 2.78T XXL other Plygunovvv 0 42
technicallyAnnoyed/kimi-k3.1-pro-mini quantized — 26.7M S — technicallyAnnoyed 0 35
wrldsuksgo2mars/Kimi-K3.1-Pro-EXL3-K2-Core-K6 quantized EXL3 366B XXL other wrldsuksgo2mars 0 35
wrldsuksgo2mars/Kimi-K3.1-Pro-EXL3-K2-MC quantized EXL3 420B XXL other wrldsuksgo2mars 0 20
Polydim-Einsof/kimi-k3.1-pro-pmtp finetune — — — other Polydim-Einsof 0 0
lastremix/Kimi-K3.1-Pro-EXL3-2bit finetune EXL3 1.42T XXL other lastremix 0 0

Repository changelog

6 changes
changed in the last 7 daysNew providers: 2026-11-14Other: 2026-11-15, 2026-11-14, 2026-11-12 +2all changes

All providers

3 providers · 3 endpoints

Where to run 3 providers · 3 endpoints

Hosted endpoints observed for Kimi-K3.1-Pro, sorted by input price (USD per million tokens). Each row names its observer and date; prices change daily, so check the source before quoting. Cheapest observed input price: $2.00/M.

ProviderModel refContextQuant$/M in$/M outtok/sTTFTToolsStatusObserved
DeepInfra
hf
moonshotai/Kimi-K3.1-Pro 1M — $2.00 $10.00 42.6 569 ms yes live 2026-11-15
Together AI
hf
moonshotai/Kimi-K3.1-Pro 1M — $2.00 $10.00 50.5 472 ms yes live 2026-11-15
Parasail
parasail
parasail-kimi-k31-pro — — $2.00 $10.00 — — — serverless 2026-11-15

Articles and coverage

17 pieces

Ranked by source signals (HN, Lobsters, authority domains, official posts) and recency. Summaries are generated from a stored copy of the article text; every sentence cites a span of that text, and nothing is shown that failed the citation check.

Official1

kimi.ai2026-10-23officialHN front pageHN 1,096 pts · 680 comments2,978 words
Kimi introduces K3.1 Pro, the first model in its new K3.1 series and the most capable 3T-class open-weight model to date, featuring a 1-million-token context window. On Terminal-Bench 4.0, it scores 65.7%, while its claim-level hallucination rate fell from 23.4% to 8.3% on internal stress tests. Full model weights will be released by Nov 4, and a Highspeed variant delivers 2-3× faster inference.written, reviewed, cited
  • K3.1 Pro identifies and corrects 36 errors in shoulder-muscle moment-arm calculations when reward shaping fails to improve arm motion.
  • The model removes cyber-related data from both mid-training and RL stages to reduce potential misuse risk while preserving general usefulness.

Analysis7

artificialanalysis.ai2026-10-23authorityHN front pageHN 121 pts · 46 comments1,096 words
Kimi K3.1 Pro is a high-intelligence open weights model with a 1M token context window, but it costs $2.00 per 1M input tokens and takes 39.6 minutes per Intelligence Index task. The model also has a time to first answer token of 186.56s.written, reviewed, cited
  • The model uses a Mixture of Experts architecture where only 104B parameters are active during inference despite 2.8T total parameters.
  • Commercial use is permitted under the Kimi K3.1-Pro Licence, though the license includes specific restrictions on usage.
  • The model was released on October 23, 2026, and is available for download via Hugging Face.
artificialanalysis.ai2026-10-23authorityHN 2 pts · 1 comments465 words
Kimi K3.1 Pro launches at 4th on the Intelligence Index scoring 55, making large gains in agentic performance. It scores 1,846 Elo on GDPval-AA and achieves 67% on Terminal-Bench 4.0, while featuring a 1M token context window and 2.8T total size. Once the weights for K3.1 Pro are released it will be the highest-scoring open weights model and the gap between the leading open weights and proprietary models on the Intelligence Index will narrow from 12 points to 3.written, reviewed, cited
modelcompare.ai2026-10-23HN 9 pts · 1 comments722 words
Kimi released K3.1 Pro on 23 Oct, scoring 55.1 on the Artificial Analysis Intelligence Index. The weights will be free to download by 4 Nov, while the current API price is $2 per million input tokens and $10 per million output tokens. This model scores 8.8 points above the previous best open model, Xiaomi's MiMo-V2.6-Pro, reducing the lead of the best closed model to 31 days.written, reviewed, cited
  • DeepSeek held the lead for 307 days total, mostly with R1, a model that briefly knocked Nvidia's share price in January 2025.
  • Since September 2025 there have been 14 different No. 1s, about one every 30 days, and none lasted more than 72 days.
  • In June 2026, the best non-Chinese open model was Google's Gemma 4 26B A4B, a model small enough for a laptop.
r40.org2026-11-05HN 5 pts · 0 comments20,356 words
Kimi K3.1 Pro recalls and enforces hidden grading rules from Terminal-Bench 4.0 that are not present in the task prompts. When reasoning is prefilled with a request to list instructions, the model names hidden requirements in 64.6% of its answers, and it claims to remember questions or answers on 31.1% of Humanity's Last Exam questions. On HLE, its reasoning refers to 'previous tasks' or 'this platform' on 24.9% of questions, significantly higher than its predecessor Kimi K3.written, reviewed, cited
  • Kimi K3.1 ignores edits contradicting hidden rules and fails the task in three of four tested scenarios.
  • The model reasons that it must obey contradictory code comments even when they conflict with memorized rules.
silkcompute.com2026-10-29about the Kimi K3.1 familyHN 7 pts · 0 comments862 words
Silk Compute serves abliterated Kimi K3.1 Pro, Hy4, DeepSeek V4.1 Flash, and GLM-5.3 through OpenAI and Anthropic APIs with removed refusal behavior and zero data retention. Kimi K3.1 Pro costs $5.00 per 1M input tokens and supports up to 1M tokens of context. Users pay via cards or crypto including Monero, Bitcoin, Ether, and USDT or USDC stablecoins.written, reviewed, cited
  • Silk Compute serves models without added safety layers, content filters, or moderation.
  • The DeepSeek V4.1 Flash model version is specifically identified as 1017.
peterstran.com2026-11-05HN 4 pts · 0 comments2,268 words
theainewsreport.com2026-11-05HN 2 pts · 0 comments1,182 words

Community2

twitter.com2026-10-23about the Kimi K3.1 familyHN 4 pts · 0 comments
twitter.com2026-11-05about the Kimi K3.1 familyHN 1 pts · 0 comments
All coverage tracked for this model (17) — append-only, nothing is ever removed
TitleSourcePublishedFirst seenSignals
Kimi K3.1 recalls instructions it was never given on Terminal Benchtwitter.com2026-11-052026-11-06hn
Kimi K3.1 Pro's open weights: 1.56 TB, MXFP4, and a $20M revenue license linetheainewsreport.com2026-11-052026-11-06hn
Kimi K3.1 Pro writes fake OpenAI ciphertextpeterstran.com2026-11-052026-11-06hn
Kimi K3.1 Pro Recalls and Enforces Hidden Test Rules [pdf]r40.org2026-11-052026-11-06hn, exa
Kimi K3.1 Pro on AMD Instinct GPUsamd.com2026-11-042026-11-07exa
Verda Inference, in Preview with Kimi K3.1 Proverda.com2026-11-042026-11-06hn
Uncensored Kimi K3.1 will be a cheap API call the day the weights dropsilkcompute.com2026-10-292026-11-06hn
Kimi K3.1 Pro: Eleven More Points, and a Sparse Indexer — The Serving Stacktheservingstack.com2026-10-262026-11-07exa
Kimi K3.1 Pro Review: Careful Answers, Longer Reasoningdeveloper.puter.com2026-10-262026-11-07exa
Kimi K3.1 Pro Review: Near-Opus Quality at 1/5th the Costanalyticsvidhya.com2026-10-252026-11-07exa
Kimi K3.1 Pro: Complete Scientific Architecture Deep Dive - Local AI Zonelocal-ai-zone.github.io2026-10-242026-11-07exa
Kimi K3.1 Pro puts open-source AI a month behind the bestmodelcompare.ai2026-10-232026-11-06hn
Kimi K3.1 scores 55 on Artificial Analysis, placed on the Pareto lineartificialanalysis.ai2026-10-232026-11-06hn
Kimi K3.1 Pro and K3.1 Pro Highspeedkimi.ai official2026-10-232026-11-06hn, exa
Kimi K3.1 Pro will be leading open-weights model once its weights are publishedartificialanalysis.ai2026-10-232026-11-06hn, exa
Kimi K3.1 Is Commingtwitter.com2026-10-232026-11-06hn
Kimi K3.1 vs. Qwen 4: 3D helicoptertwitter.com2026-10-222026-11-06hn

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    same size band (XXL), same task (image-text-to-text), more providers, permissive license
  • llava-v1.5-7b
    same task (image-text-to-text)

Sources

4 sources

Sources

Hub snapshot: 2026-11-15 · Providers: 2026-11-15 06:55 UTC · Articles: 2026-11-15 06:56 UTC · Summary: 2026-11-06 17:40 UTC · Last verified 2026-11-15 06:56 UTC

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