The best open LLMs for your use case:
Next-generation reasoning model from MiniMax with frontier agentic, coding, and multimodal performance. Strong scores on SWE-Bench, BrowseComp, OmniDocBench, and IMO/USAMO competition reasoning.
Speed:
Intelligence:
Price: (1M Tokens)
$0.30 / 1.20Cached input: (1M Tokens)
$0.06Context: (tokens)
524,288Inputs:
Benchmarks:
MMMU-Pro
Multimodal - Vision
Video-MME v2
Multimodal - Vision
GPQA-Diamond
General Knowledge
Claw-Eval
Agents and Function Calling
SWE-Bench Verified
Coding Agents
SWE-Bench Pro
Coding Agents
Apex Agents
Agents and Function Calling
MMMU-Pro
Multimodal - Vision
Video-MME v2
Multimodal - Vision
GPQA-Diamond
General Knowledge
Claw-Eval
Agents and Function Calling
SWE-Bench Verified
Coding Agents
SWE-Bench Pro
Coding Agents
Apex Agents
Agents and Function Calling
1T-parameter MoE flagship from Moonshot with long-horizon coding, agent swarms scaling to 300 sub-agents, and state-of-the-art reasoning.
Speed:
Intelligence:
Price: (1M Tokens)
$1.20 / 4.50Cached input: (1M Tokens)
$0.20Context: (tokens)
262,144Inputs:
Benchmarks:
MMMU-Pro
Multimodal - Vision
SciCode
Coding Agents
MCP-Mark
Agents and Function Calling
Apex Agents
Agents and Function Calling
FrontierCode
Coding Agents
LiveCodeBench
Coding Agents
Terminal-Bench 2.0
Coding Agents
Claw-Eval
Agents and Function Calling
MMMU-Pro
Multimodal - Vision
SciCode
Coding Agents
MCP-Mark
Agents and Function Calling
Apex Agents
Agents and Function Calling
FrontierCode
Coding Agents
LiveCodeBench
Coding Agents
Terminal-Bench 2.0
Coding Agents
Claw-Eval
Agents and Function Calling
Use case:
Multimodal - Vision
Features:
Long Context Handling