Open models
caught the frontier.
Kimi K3's weights are out. The open frontier now holds 93% of the top score, 4 points off the frontier, on weights you can take anywhere.
Gap in 2024
0 pts
Gap today
0 pts
Open leader
0
Kimi K3 · weights out015 open source
0Kimi K3
0.0×best open vs best closed
0incl. first-party APIs
One index hides the fit. Pick your use case.
Every model on one chart
The whole field on one composite index: filter, sort, and inspect any model.
AttributedArtificial Analysis v4.1
Leaderboard
| Model | |||||
|---|---|---|---|---|---|
| 1 | DeepSeek V4 Flash 0731 | 50 | 69.4 | $72 | |
| 2 | gpt-oss-20b | 15 | 41.2 | $36 | |
| 3 | GPT-5.6 Luna | 51 | 29.3 | $174 | |
| 4 | DeepSeek V4 Pro | 44 | 25.0 | $176 | |
| 5 | gpt-oss-120b | 24 | 24.9 | $96 | |
| 6 | MiniMax-M3 | 44 | 21.6 | $204 | |
| 7 | Llama 3.3 70Bopen | 9 | 11.2 | $81 | |
| 8 | Muse Spark 1.1 | 51 | 9.3 | $548 |
Kimi K3
57
2.3
$2.4K
1M
$3.00 / $15.0
$0.30
Agents
50
Coding
76
GPQA
94
HLE
44
Long context
75
Open is catching up, fast
The open frontier gained 48 index points in under two years. Kimi K3's weights shipped July 27 and cut the gap to 4 points, the closest open has ever been.
AttributedArtificial Analysis (historical)
Run the open frontier yourself.
Same OpenAI-compatible API, open weights you keep, at a fraction of closed-API cost.
Copied
# uv add together
from together import Together
client = Together()
response = client.chat.completions.create(
model="moonshotai/Kimi-K3",
messages=[{"role": "user", "content": "What are the top 3 things to do in New York?"}],
)
print(response.choices[0].message.content)