Kimi K2 Instruct 0905 kimi-k2-0905

moonshotai · kimi agentic

unranked — no quality signals yet

params
1000B (A32B)
arch
moe
context
256k
license
modified-mit open weights
released
Sep 2025
downloads/30d
1.1M

# why ranked

Overall: provisional — score 23.5 ● low — a single signal; treat with caution

provisional: too few independent signals for a numbered position — the score is shown, but this model sorts after every ranked model.

signalweightinput (0–100)
aa_intelligence 0.50 23.5
arena_elo 0.30
bench_composite 0.20

missing signals are dropped and the remaining weights renormalized — never imputed.

Coding: provisional — score 100.0 ● low — a single signal; treat with caution

provisional: too few independent signals for a numbered position — the score is shown, but this model sorts after every ranked model.

signalweightinput (0–100)
aa_coding 0.25
aider_polyglot 0.25
arena_elo_code 0.15
swe_bench_verified 0.35 100.0

missing signals are dropped and the remaining weights renormalized — never imputed.

Agentic: #1 — score 100.0 ● low — a single signal; treat with caution

signalweightinput (0–100)
swe_bench_verified 1.00 100.0

full methodology

# trend

OGM score · last 2 days
OGM score over 2 days

# benchmarks

benchmarkscoresourcedate
AA Intelligence Index 23.5 Artificial Analysis
AA Math Index 57.3 Artificial Analysis
AIME 2024 0.7 / 1 LLM Stats
SWE-bench Verified 71.2 SWE-bench Oct 2025

# where to run

providerquantctx$/M in$/M out$/M blendtpsuptime
Novitafp8 256k $0.60$2.50$1.07 99.7%
Groqunknown 256k $1.00$3.00$1.50 99.9%

blended = (3·input + output) / 4 per 1M tokens · cheapest first

source aliases
aa
kimi-k2-0905
openrouter
moonshotai/kimi-k2-0905
swebench
kimi-k2-0905-preview