Model Comparison

DeepSeek-V3.1 vs MiniMax M1 80K

DeepSeek-V3.1 shows notably better performance in the majority of benchmarks. DeepSeek-V3.1 is 2.1x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

8 benchmarks

DeepSeek-V3.1 outperforms in 5 benchmarks (GPQA, Humanity's Last Exam, MMLU-Pro, SimpleQA, SWE-Bench Verified), while MiniMax M1 80K is better at 3 benchmarks (AIME 2024, AIME 2025, LiveCodeBench).

DeepSeek-V3.1 shows notably better performance in the majority of benchmarks.

Thu Apr 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.1 costs less

For input processing, DeepSeek-V3.1 ($0.27/1M tokens) is 2.0x cheaper than MiniMax M1 80K ($0.55/1M tokens).

For output processing, DeepSeek-V3.1 ($1.00/1M tokens) is 2.2x cheaper than MiniMax M1 80K ($2.20/1M tokens).

In conclusion, MiniMax M1 80K is more expensive than DeepSeek-V3.1.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Apr 16 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.1
Input tokens$0.27
Output tokens$1.00
Best providerDeepinfra
MiniMax
MiniMax M1 80K
Input tokens$0.55
Output tokens$2.20
Best providerNovita
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Model Size

Parameter count comparison

215.0B diff

DeepSeek-V3.1 has 215.0B more parameters than MiniMax M1 80K, making it 47.1% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
MiniMax
MiniMax M1 80K
456.0Bparameters
671.0B
DeepSeek-V3.1
456.0B
MiniMax M1 80K

Context Window

Maximum input and output token capacity

MiniMax M1 80K accepts 1,000,000 input tokens compared to DeepSeek-V3.1's 163,840 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while MiniMax M1 80K is limited to 40,000 tokens.

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
MiniMax
MiniMax M1 80K
Input1,000,000 tokens
Output40,000 tokens
Thu Apr 16 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek-V3.1

MIT

Open weights

MiniMax M1 80K

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while MiniMax M1 80K was released on 2025-06-16.

MiniMax M1 80K is 5 months newer than DeepSeek-V3.1.

DeepSeek-V3.1

Jan 10, 2025

1.3 years ago

MiniMax M1 80K

Jun 16, 2025

10 months ago

5mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-V3.1 is available from DeepInfra, Novita. MiniMax M1 80K is available from Novita.

DeepSeek-V3.1

deepinfra logo
Deepinfra
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M
novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M

MiniMax M1 80K

novita logo
Novita
Input Price:Input: $0.55/1MOutput Price:Output: $2.20/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
Higher GPQA score (74.9% vs 70.0%)
Higher Humanity's Last Exam score (15.9% vs 8.4%)
Higher MMLU-Pro score (83.7% vs 81.1%)
Higher SimpleQA score (93.4% vs 18.5%)
Higher SWE-Bench Verified score (66.0% vs 56.0%)
MiniMax
Larger context window (1,000,000 tokens)
Higher AIME 2024 score (86.0% vs 66.3%)
Higher AIME 2025 score (76.9% vs 49.8%)
Higher LiveCodeBench score (65.0% vs 56.4%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.1
MiniMax
MiniMax M1 80K

FAQ

Common questions about DeepSeek-V3.1 vs MiniMax M1 80K

DeepSeek-V3.1 shows notably better performance in the majority of benchmarks. DeepSeek-V3.1 is made by DeepSeek and MiniMax M1 80K is made by MiniMax. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. MiniMax M1 80K scores MATH-500: 96.8%, ZebraLogic: 86.8%, AIME 2024: 86.0%, MMLU-Pro: 81.1%, AIME 2025: 76.9%.
DeepSeek-V3.1 is 2.0x cheaper for input tokens. DeepSeek-V3.1 costs $0.27/M input and $1.00/M output via deepinfra. MiniMax M1 80K costs $0.55/M input and $2.20/M output via novita.
DeepSeek-V3.1 supports 164K tokens and MiniMax M1 80K supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (164K vs 1.0M), input pricing ($0.27 vs $0.55/M). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.1 is developed by DeepSeek and MiniMax M1 80K is developed by MiniMax.