Three models, three price points, one question: how much quality do you lose by going cheap?

The numbers

	MiniMax M2.7	Claude Opus 4.6	DeepSeek Chat
Input price	$0.30/1M	$15.00/1M	$0.27/1M
Output price	$1.20/1M	$75.00/1M	$1.10/1M
Speed	100 tok/s	50 tok/s	60 tok/s
SWE-Pro	56.22%	57.3%	~54%
Context	200K	200K	128K
Params	230B MoE (10B active)	Unknown	671B MoE (37B active)
Monthly cost (3hr/day)	~$5	~$150	~$4

Quality comparison

Complex refactoring: Claude Opus wins. It produces the cleanest, most thoughtful code. M2.7 is close (~90%) but occasionally misses edge cases that Opus catches.

Routine coding: M2.7 and DeepSeek are both good enough. The 10% quality gap vs Opus is invisible for standard feature implementation, bug fixes, and test writing.

Speed: M2.7 wins at 100 tok/s. Noticeably faster than both Claude (50) and DeepSeek (60). For interactive coding, this matters.

Long sessions: M2.7’s self-evolving capability helps it maintain coherence over longer tasks. DeepSeek can drift. Claude is the most consistent.

The smart approach

Use all three with model routing:

1. M2.7 or DeepSeek for routine work ($0.30/1M) — 80% of your tasks
2. Claude Opus for hard problems ($15/1M) — 20% of your tasks

This gives you 95% of the “Claude for everything” experience at 20% of the cost. See our cheapest AI coding setup guide.

M2.7 vs DeepSeek specifically

These two are the closest competitors:

	M2.7	DeepSeek Chat
Price	$0.30/1M	$0.27/1M
Speed	100 tok/s	60 tok/s
SWE-Pro	56.22%	~54%
Self-evolving	✅	❌
Reasoning model	Built-in	Separate (Reasoner)

M2.7 is slightly more expensive but faster and scores higher. DeepSeek has a separate Reasoner model for complex tasks. For most developers, the difference is negligible — pick whichever is available on your preferred platform.

Both are available on OpenRouter and work with Aider.

Related: MiniMax M2.7 Complete Guide · How to Reduce LLM API Costs · When to Use Small vs Frontier Models