Compare the listed model data for DeepSeek-R1 by DeepSeek and MiniMax-M1 (80k) by MiniMax. Benchmark and pricing records are not a controlled test and may change.
Data last updated: 2026-10-16. Verify current model details with each provider.
What the listed data says
DeepSeek-R1: 128K tokens; MiniMax-M1 (80k): 1M tokens. MiniMax-M1 (80k) has the larger listed context window. DeepSeek-R1 is listed for coding, reasoning, long-context tasks; MiniMax-M1 (80k) is listed for coding, reasoning, agentic workflows, long-context tasks. Shared catalog benchmark entries: GPQA Diamond: DeepSeek-R1 71.5%; MiniMax-M1 (80k) 67.8%; SWE-bench Verified: DeepSeek-R1 49.2%; MiniMax-M1 (80k) 56.4%; LiveCodeBench: DeepSeek-R1 65.9%; MiniMax-M1 (80k) 62.9%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
Catalog source links
Use these model and provider links to verify current specifications, pricing, and availability.
The first listed parameter quantities are 671B total (37B active via MoE) and 456B total (45.9B active via MoE); the larger quantity is 1.47× the smaller. Total and active MoE parameters are not directly equivalent.
The catalog release dates are January 2025 and May 2025, about 4 months apart at the precision supplied.
Cost example: 1M input and 1M output tokens
A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.
Choose DeepSeek-R1 if…
Choose DeepSeek-R1 when your task aligns with catalog-listed uses or strengths such as Competition mathematics and proof verification, Advanced software engineering: debugging complex systems, production-grade algorithms, Scientific research in physics, chemistry, biology, Enterprise AI agents needing transparent, auditable reasoning.
Choose MiniMax-M1 (80k) if…
Choose MiniMax-M1 (80k) when your task aligns with catalog-listed uses or strengths such as Entire-repository code analysis, Multi-book research synthesis, Long-running agentic workflows, 1 million token context — entire software repositories in one session.
Feature Comparison — DeepSeek-R1 vs MiniMax-M1 (80k)
Catalog specifications for DeepSeek-R1 and MiniMax-M1 (80k)
Specification
DeepSeek-R1
MiniMax-M1 (80k)
Provider
DeepSeek
MiniMax
Parameters
671B total (37B active via MoE)
456B total (45.9B active via MoE)
Context window
128K tokens
1M tokens
Maximum output
Not listed
Not listed
Catalog pricing
Open source MIT license — free to self-host. DeepSeek API: $0.14/MTok input (cache hit), $0.55/MTok input, $2.19/MTok output
MiniMax API pricing; weights released for research
Listed input/output cost per 1M tokens
input $0.55, output $2.19 per 1M tokens
Separate numeric input/output rates not listed
License
MIT
MiniMax Model License
Coding support
Listed
Listed
Reasoning support
Listed
Listed
Vision input
Not listed
Not listed
Multimodal
Not listed
Not listed
Open weights
Yes
Yes
Benchmark: GPQA Diamond
71.5%
67.8%
Benchmark: SWE-bench Verified
49.2%
56.4%
Benchmark: LiveCodeBench
65.9%
62.9%
Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.
Frequently Asked Questions
What is different between DeepSeek-R1 and MiniMax-M1 (80k)?
DeepSeek-R1: 128K tokens; MiniMax-M1 (80k): 1M tokens. MiniMax-M1 (80k) has the larger listed context window. DeepSeek-R1 is listed for coding, reasoning, long-context tasks; MiniMax-M1 (80k) is listed for coding, reasoning, agentic workflows, long-context tasks. Shared catalog benchmark entries: GPQA Diamond: DeepSeek-R1 71.5%; MiniMax-M1 (80k) 67.8%; SWE-bench Verified: DeepSeek-R1 49.2%; MiniMax-M1 (80k) 56.4%; LiveCodeBench: DeepSeek-R1 65.9%; MiniMax-M1 (80k) 62.9%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
What benchmark values are listed for DeepSeek-R1 and MiniMax-M1 (80k)?
GPQA Diamond: DeepSeek-R1 71.5%; MiniMax-M1 (80k) 67.8%; SWE-bench Verified: DeepSeek-R1 49.2%; MiniMax-M1 (80k) 56.4%; LiveCodeBench: DeepSeek-R1 65.9%; MiniMax-M1 (80k) 62.9%. The catalog values may use different versions and evaluation setups, so they are reference points rather than a controlled head-to-head result.
Which model has the larger listed context window?
DeepSeek-R1: 128K tokens; MiniMax-M1 (80k): 1M tokens. MiniMax-M1 (80k) has the larger listed context window.
What are the listed costs per million tokens for DeepSeek-R1 and MiniMax-M1 (80k)?
DeepSeek-R1: input $0.55, output $2.19 per 1M tokens (Open source MIT license — free to self-host. DeepSeek API: $0.14/MTok input (cache hit), $0.55/MTok input, $2.19/MTok output). MiniMax-M1 (80k): Separate numeric input/output rates not listed (MiniMax API pricing; weights released for research). Where separate numeric input and output rates are available, the worked example uses 1M input plus 1M output tokens. Confirm current terms with each provider.
How far apart are the listed release dates for DeepSeek-R1 and MiniMax-M1 (80k)?
The catalog lists DeepSeek-R1 as January 2025 and MiniMax-M1 (80k) as May 2025, about 4 months apart at the precision supplied.
When was the comparison data last updated?
The model catalog records 2026-10-16 as its data update date. Provider specifications and prices may have changed since then.
How should I choose between DeepSeek-R1 and MiniMax-M1 (80k)?
Compare the listed specifications and capabilities, review the benchmark notes, then test both with the same representative prompt for your task. This page does not claim a universal winner.
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