MiniMax M3 vs DeepSeek V3.2
Benchmark Performance
Available Benchmarks
| Benchmark | MiniMax-M3 | DeepSeek-V3.2 |
|---|---|---|
| LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader | 1,435.20100% of row best · rating · minimax-m3; 95% CI [1430.86827835, 1439.53977389]; votes 44544; rank 77 | 1,424.8399% of row best · rating · deepseek-v3.2; 95% CI [1421.30044809, 1428.36162643]; votes 46487; rank 91 |
| Overall ResultCounted from the protocol-matched rows above | 1 benchmark winOverall lead | 0 benchmark wins |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Technical Differences
Side-by-Side Facts
| Field | MiniMax-M3 | DeepSeek-V3.2 |
|---|---|---|
| Developer | MiniMax | DeepSeek |
| Family | Minimax M3 | Deepseek V3 2 |
| Model | MiniMax-M3 | DeepSeek-V3.2 |
| Version | MiniMax-M3 | DeepSeek-V3.2 |
| Lifecycle | active | active |
| Released | 2026-06-01 | 2025-12-01 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,049K | 164K |
| Total parameters | 427B | 685.4B |
| Active parameters | 23B | Unknown |
| License | other | mit |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning |
16 comparable fields · 11 material differences · Pair passes the primary-source comparison gate
MiniMax M3 Capabilities
DeepSeek V3.2 Capabilities
Internal Comparison Graph
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|---|---|---|---|
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MiniMax-M3MiniMax | vs |  GLM-5.3Z.ai | cross-developer peerstext |
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MiniMax-M3MiniMax | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
MiniMax M3 vs DeepSeek V3.2 FAQs
Is MiniMax M3 or DeepSeek V3.2 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both MiniMax M3 and DeepSeek V3.2, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, MiniMax M3 or DeepSeek V3.2?+
MiniMax M3 is $0.28 and DeepSeek V3.2 is $0.26 per million tokens, so DeepSeek V3.2 is cheaper on this metric. MiniMax M3 is $1.10 and DeepSeek V3.2 is $0.38 per million tokens, so DeepSeek V3.2 is cheaper on this metric.
Which has a larger context window, MiniMax M3 or DeepSeek V3.2?+
MiniMax M3 has the larger sourced context window. MiniMax M3 supports 1,049K and DeepSeek V3.2 supports 164K.
Which performs better in benchmarks, MiniMax M3 or DeepSeek V3.2?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can MiniMax M3 or DeepSeek V3.2 be self-hosted?+
Both models have the same recorded self-hosting status: supported. MiniMax M3 is open weight; DeepSeek V3.2 is open weight.
Can MiniMax M3 and DeepSeek V3.2 understand images?+
MiniMax M3 is documented with image input; DeepSeek V3.2 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, MiniMax M3 or DeepSeek V3.2?+
Neither has a larger sourced maximum output. MiniMax M3 is — and DeepSeek V3.2 is —.
Do MiniMax M3 and DeepSeek V3.2 support reasoning and tool use?+
MiniMax M3: reasoning, tool calling, and image input. DeepSeek V3.2: reasoning. Feature support does not establish relative quality.
Which is available from more inference providers, MiniMax M3 or DeepSeek V3.2?+
MiniMax M3 has 5 sourced provider routes; DeepSeek V3.2 has 3, so MiniMax M3 has broader tracked availability.
Which offers better value, MiniMax M3 or DeepSeek V3.2?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.