MiniMax · Open weights
MiniMax Latest
Compatibility alias for MiniMax M3 Thinking, retaining its existing request format and structured-output support. The newer MiniMax M3.1 Flash is available separately as minimax/minimax-m3.1-flash and has different request parameter support.
- Reasoning
- Tools
- Vision
- Structured output
- Input
- Text, Images
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.23
- Output
- $0.96
- Cache read
- $0.05
Reference prices as published by the model provider. API example
Specifications
- Context window
- 512K
- Max output
- 80K
Side by side
MiniMax Latest compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| MiniMax LatestMiniMaxThis model | GPT 6 LunaOpenAIRemove | |
|---|---|---|
| Provider | MiniMax | OpenAI |
| Discovery tier | Open weights | Efficient |
| Added | May 3, 2026 | Sep 22, 2026 |
| Limits | ||
| Context window | 512K | 1.05MBest |
| Max output | 80K | 128KBest |
| Average output | — | 120 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.23 | $0.10Best |
| Output | $0.96 | $0.50Best |
| Cache read | $0.05 | $0.01Best |
| Cache write | — | $0.13 |
| Performance | ||
| Throughput | 170.7 tok/sBest | 68.2 tok/s |
| Time to first token | 1.2 sBest | 4.9 s |
| Request success (24h) | 99.9%Best | 99.8% |
| Benchmark indexes | ||
| Intelligence Index | 29.2 | 29.9Best |
| Coding Index | 58.6 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Structured output | Yes | Yes |
| PDF input | No | Yes |
| Reasoning effort | — | none, low, medium, high, xhigh, max |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- MiniMax Latest
- GPT 6 Luna
Intelligence Index
- MiniMax Latest29.2
- GPT 6 Luna29.9
MiniMax Latest: Better than 70% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- MiniMax Latest: 58.6
- GPT 6 Luna: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- MiniMax Latest: 21.3%
- GPT 6 Luna: 40.5%Top
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- MiniMax Latest: 4.4%
- GPT 6 Luna: 10.2%Top
Harvey LAB-AAv1.1
Legal tasks passed in full, with no material hallucination
- MiniMax Latest: 0.0%
- GPT 6 Luna: —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- MiniMax Latest: 1,089 Elo
- GPT 6 Luna: 1,097 EloTop
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- MiniMax Latest: 1,243 Elo
- GPT 6 Luna: 1,263 EloTop
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- MiniMax Latest: 9.8%
- GPT 6 Luna: 13.8%Top
AA-LCRv1.1
Reasoning across long documents
- MiniMax Latest: 83.0%Top
- GPT 6 Luna: 78.3%
MLCR-AA
Long-context reasoning over medical records
- MiniMax Latest: 4.4%
- GPT 6 Luna: 18.3%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- MiniMax Latest: 39.0%Top
- GPT 6 Luna: 28.3%
GPQA Diamond
Graduate-level science questions
- MiniMax Latest: 92.9%
- GPT 6 Luna: —
IFBench
Following precise output instructions
- MiniMax Latest: 82.9%
- GPT 6 Luna: —
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- MiniMax Latest: 2.0%
- GPT 6 Luna: 2.5%Top
SciCode
Scientific computing in Python
- MiniMax Latest: 47.1%
- GPT 6 Luna: 50.9%Top
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- MiniMax Latest: 42.4%
- GPT 6 Luna: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- MiniMax Latest: 88.9%
- GPT 6 Luna: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- MiniMax Latest: 83.0%Top
- GPT 6 Luna: 78.3%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- MiniMax Latest
- GPT 6 Luna
| Leaderboard | MiniMax Latest | GPT 6 Luna |
|---|---|---|
| ARC-AGI-3 (Default harness) | Not in top 20 | #18 · 0.2% |
Ranks among Noumen catalog models on ARC Prize leaderboards. Only top-20 placements are listed.ARC Prize
- MiniMax Latest
- GPT 6 Luna
| Leaderboard | MiniMax Latest | GPT 6 Luna |
|---|---|---|
| SVG | Not in top 20 | #16 · 1250 |
Ranks among Noumen catalog models on Design Arena leaderboards. Only top-20 placements are listed.Design Arena
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Throughput
- 170.7 tok/s
- Faster than 80% of 251 models
- Time to first token
- 1.2 s
- Quicker than 92% of 251 models
- Prompt cache hits
- 80.3%
- About $0.0854 per 1M input tokens with caching
- Request success (24h)
- 99.9%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "minimax/minimax-latest",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="minimax/minimax-latest",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)MiniMax
Related models
Other MiniMax models, starting with the same family.