Kimi K2.5 kimi-k2.5

moonshotai · kimi reasoning flagship

#9 overall

params
1059B (A32B)
arch
moe
context
256k
license
modified-mit open weights
released
Feb 2026
reasoning
yes
train compute
5.8e+24 FLOP
downloads/30d
1.3M

# why ranked

Overall: #9 — score 43.5 ● medium — one signal missing, weights renormalized

signalweightinput (0–100)
aa_intelligence 0.50 38.1
arena_elo 0.30
bench_composite 0.20 56.9

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

full methodology

# trend

collecting history — trends appear after a few daily runs.

# benchmarks

benchmarkscoresourcedate
AA Intelligence Index 38.1 Artificial Analysis
Aa-lcr 0.7 / 1 LLM Stats
AIME 2025 1.0 / 1 LLM Stats
Browsecomp 0.7 / 1 LLM Stats
Charxiv-r 0.8 / 1 LLM Stats
Cybergym 0.4 / 1 LLM Stats
Deepsearchqa 0.8 / 1 LLM Stats

# where to run

providerquantctx$/M in$/M out$/M blendtpsuptime
ModelRunfp4 256k $0.40$1.90$0.78 100.0%
DigitalOceanunknown 250k $0.38$2.02$0.79 99.1%
Chutesint4 256k $0.44$2.00$0.83 83.9%
DeepInfrafp4 256k $0.45$2.25$0.90 99.7%
SiliconFlowint4 256k $0.45$2.25$0.90 100.0%
AtlasCloudint4 256k $0.49$2.50$0.99 100.0%
StreamLakefp8 250k $0.54$2.70$1.08 99.9%
Novitaunknown 256k $0.57$2.85$1.14 100.0%
Moonshot AIint4 256k $0.60$3.00$1.20 100.0%
Phalaunknown 256k $0.60$3.00$1.20
Veniceunknown 250k $0.56$3.50$1.29

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

source aliases
aa
kimi-k2.5
epoch
Kimi K2.5
llmstats
kimi-k2.5
openrouter
moonshotai/kimi-k2.5