| Signal | DeepSeek V3 | Delta | MiniMax M2.1 |
|---|---|---|---|
Capabilities | 50 | -17 | |
Benchmarks | 70 | 0 | |
Pricing | 99 | -- | |
Context window size | 83 | -1 | |
Recency | 42 | -58 | |
Output Capacity | 70 | -18 | |
| Overall Result | 0 wins | of 6 | 5 wins |
Score History
69.5
current score
MiniMax M2.1
right now
69.9
current score
DeepSeek
MiniMax
| Metric | DeepSeek V3 | MiniMax M2.1 | Winner |
|---|---|---|---|
| Overall Score | 70 | 70 | MiniMax M2.1 |
| Rank | #102 | #100 | MiniMax M2.1 |
| Quality Rank | #102 | #100 | MiniMax M2.1 |
| Adoption Rank | #102 | #100 | MiniMax M2.1 |
| Parameters | -- | -- | -- |
| Context Window | 164K | 197K | MiniMax M2.1 |
| Pricing | $0.32/$0.89/M | $0.29/$0.95/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | MiniMax M2.1 |
| Benchmarks | 70 | 70 | MiniMax M2.1 |
| Pricing | 99 | 99 | DeepSeek V3 |
| Context window size | 83 | 84 | MiniMax M2.1 |
| Recency | 42 | 100 | MiniMax M2.1 |
| Output Capacity | 70 | 88 | MiniMax M2.1 |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 70/100 (rank #102), placing it in the top 65% of all 290 models tracked.
Scores 70/100 (rank #100), placing it in the top 66% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. DeepSeek V3 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (197K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.89/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (70/100) correlates with better nuance, coherence, and style in long-form content
DeepSeek V3 and MiniMax M2.1 are extremely close in overall performance (only 0.4000000000000057 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
DeepSeek V3
Marginally better benchmark scores; both are excellent
Best for Cost
DeepSeek V3
2% lower pricing; better value at scale
Best for Reliability
DeepSeek V3
Higher uptime and faster response speeds
Best for Prototyping
DeepSeek V3
Stronger community support and better developer experience
Best for Production
DeepSeek V3
Wider enterprise adoption and proven at scale
by DeepSeek
| Capability | DeepSeek V3 | MiniMax M2.1 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
DeepSeek
MiniMax
DeepSeek V3 saves you $0.0180/month
That's 1% cheaper than MiniMax M2.1 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | DeepSeek V3 | MiniMax M2.1 |
|---|---|---|
| Context Window | 164K | 197K |
| Max Output Tokens | 16,384 | 196,608 |
| Open Source | Yes | Yes |
| Created | Dec 26, 2024 | Dec 23, 2025 |