GLM-5.3 vs MiniMax M3: Specs & Benchmark Comparison
| Characteristic | GLM-5.3 | MiniMax M3 |
|---|---|---|
| Company | Zhipu AI | MiniMax |
| Release Date | August 14, 2026 | June 1, 2026 |
| Parameters | 753B | 428B |
| Multimodal | No | Yes |
| Context (input) | 1.0M | 1.0M |
| Context (output) | 131K | 131K |
| Input Price / 1M | $1.40 | $0.30 |
| Output Price / 1M | $4.40 | $1.20 |
| Average Score | 0.8 | 0.9 |
Verdict
Both models show equal results — the choice depends on your specific use case.
Overall Performance
Both models show comparable average scores: GLM-5.3 — 0.8, MiniMax M3 — 0.9.
API Cost
MiniMax M3 is 3.9x cheaper: input $0.30/1M vs $1.40/1M tokens.
Context Window
Same context size: 1M tokens.
Recency
GLM-5.3 is newer: released 8/14/2026 vs 6/1/2026.
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Frequently Asked Questions
Which is better for coding — GLM-5.3 or MiniMax M3?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — GLM-5.3 or MiniMax M3?
MiniMax M3 is cheaper for input: $0.30 per 1M tokens vs $1.40.
Which has a larger context window — GLM-5.3 or MiniMax M3?
GLM-5.3 supports a larger context: 1,000,000 tokens vs 1,000,000.
The GLM-5.3 and MiniMax M3 comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the GLM-5.3 or MiniMax M3 page. See also the complete list of AI model comparisons.