The best open LLMs for your use case:
Moonshot AI's 2.8-trillion-parameter open-weight frontier model with native vision, 1M-token context, and state-of-the-art agentic coding and tool use.
Speed:
Intelligence:
Price: (1M Tokens)
$3.00 / 15.00Cached input: (1M Tokens)
$0.30Context: (tokens)
1,048,576Inputs:
Benchmarks:
HLE
General Knowledge
GPQA-Diamond
General Knowledge
MMMU-Pro
Multimodal - Vision
Terminal-Bench 2.1
Coding Agents
FrontierSWE
Coding Agents
DeepSWE
Coding Agents
Program Bench
Coding Agents
MCP-Atlas
Agents and Function Calling
HLE
General Knowledge
GPQA-Diamond
General Knowledge
MMMU-Pro
Multimodal - Vision
Terminal-Bench 2.1
Coding Agents
FrontierSWE
Coding Agents
DeepSWE
Coding Agents
Program Bench
Coding Agents
MCP-Atlas
Agents and Function Calling
Try it outDeepSeek's frontier 1.6T-parameter Mixture-of-Experts model (49B active per token) with hybrid attention built for long-context, low-cost reasoning. Runs in FP4 with a 512K-token context window.
Speed:
Intelligence:
Price: (1M Tokens)
$1.74 / 3.48Cached input: (1M Tokens)
$0.20Context: (tokens)
512,000Inputs:
Benchmarks:
GPQA-Diamond
General Knowledge
HLE
General Knowledge
MMLU-Pro
General Knowledge
SimpleQA
General Knowledge
LiveCodeBench
Coding Agents
SWE-Bench Verified
Coding Agents
Terminal-Bench 2.0
Coding Agents
GDPval-AA
Agents and Function Calling
GPQA-Diamond
General Knowledge
HLE
General Knowledge
MMLU-Pro
General Knowledge
SimpleQA
General Knowledge
LiveCodeBench
Coding Agents
SWE-Bench Verified
Coding Agents
Terminal-Bench 2.0
Coding Agents
GDPval-AA
Agents and Function Calling
Use case:
General Knowledge