Which is better for coding — GLM-4.7-Flash or MiniMax M2.1?

Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.

Which model is cheaper — GLM-4.7-Flash or MiniMax M2.1?

GLM-4.7-Flash is cheaper for input: $0.07 per 1M tokens vs $0.30.

Which has a larger context window — GLM-4.7-Flash or MiniMax M2.1?

MiniMax M2.1 supports a larger context: 1,000,000 tokens vs 128,000.

GLM-4.7-Flash vs MiniMax M2.1: Specs & Benchmark Comparison

Characteristic	GLM-4.7-Flash	MiniMax M2.1
Company	Zhipu AI	MiniMax
Release Date	January 18, 2026	December 22, 2025
Parameters	30B	—
Multimodal	No	No
Context (input)	128K	1.0M
Context (output)	16K	100K
Input Price / 1M	$0.07	$0.30
Output Price / 1M	$0.40	$1.20
Average Score	0.6	0.9
Benchmarks
GPQA	0.8	0.8

Visual Benchmark Comparison

GLM-4.7-Flash

MiniMax M2.1

GPQA0.8 vs 0.8

0.8

Verdict

GLM-4.7-Flash leads in 2 out of 4 comparison categories.

Overall Performance

Both models show comparable average scores: GLM-4.7-Flash — 0.6, MiniMax M2.1 — 0.9.

API Cost

GLM-4.7-Flash is 3.2x cheaper: input $0.07/1M vs $0.30/1M tokens.

Context Window

MiniMax M2.1 supports a larger context: 1M vs 128K tokens.

Recency

GLM-4.7-Flash is newer: released 1/18/2026 vs 12/22/2025.

More About These Models

GLM-4.7-Flash

Zhipu AI — specs, benchmarks, API

MiniMax M2.1

MiniMax — specs, benchmarks, API

Related Comparisons

GLM-4.7-Flash vs GLM-5 GLM-4.5 vs GLM-4.7-Flash GLM-4.7-Flash vs GPT-5.2 Codex GLM-4.7-Flash vs Mercury 2 GLM-4.7-Flash vs MiniMax M2.5 GLM-4.7-Flash vs GPT-5.3 Codex

All model comparisons →

The GLM-4.7-Flash and MiniMax M2.1 comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the GLM-4.7-Flash or MiniMax M2.1 page. See also the complete list of AI model comparisons.