AI model comparison
MiniMax M3.1 Flash vs GLM 5.3
Side by side comparison of MiniMax M3.1 Flash and GLM 5.3 on pricing, benchmark scores, context window, and more.
MiniMax-M3.1-Flash is a multimodal model from MiniMax. Compared with M3, it delivers significant improvements across multiple benchmarks, particularly in complex agentic tasks, coding, and cybersecurity.
- Input / 1M
- $0.15
- Output / 1M
- $0.60
- Context
- 1M
GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks.
- Input / 1M
- $0.08
- Output / 1M
- $1.40
- Context
- 1.05M
Comparing image generators? Compare image models
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
MiniMax M3.1 Flash
1.4x cheaper for a typical chat
Higher intelligence score
GLM 5.3
44.8 vs 42.7 on Artificial Analysis
Larger context window
GLM 5.3
1.05M vs 1M tokens
Newer release
MiniMax M3.1 Flash
Released October 19, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
MiniMax M3.1 Flash vs GLM 5.3 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.15 | $0.08 |
| Output tokensPer 1M tokens | $0.60 | $1.40 |
| Cached input (read)Per 1M tokens | $0.02 | $0.08 |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 1M tokens | 1.05M tokens |
| Max output | 524K tokens | 944K tokens |
| Input types | Image, Text, Video | Text |
| Output types | Text | Text |
| Reasoning effort levels | Max, Extra high, High, Medium, Low | Max, High, Low |
| Default reasoning effort | Max | Max |
| Release date | October 19, 2026 | August 18, 2026 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Not supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Not supported | Supported |
| Deterministic seed | Not supported | Supported |
| Verbosity control | Not supported | Not supported |
Our take
MiniMax M3.1 Flash is 1.4x cheaper for a typical chat. GLM 5.3 scores higher on the Artificial Analysis Intelligence Index (44.8 vs 42.7). GLM 5.3 has the larger context window (1.05M vs 1M tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is MiniMax M3.1 Flash or GLM 5.3 cheaper?
MiniMax M3.1 Flash is cheaper for a typical chat (2K input tokens and 500 output tokens). MiniMax M3.1 Flash costs $0.15 per 1M input tokens and $0.60 per 1M output tokens, while GLM 5.3 costs $0.08 per 1M input tokens and $1.40 per 1M output tokens.
Which has a bigger context window, MiniMax M3.1 Flash or GLM 5.3?
GLM 5.3 supports up to 1.05M tokens of context, compared with 1M for MiniMax M3.1 Flash.
Is MiniMax M3.1 Flash smarter than GLM 5.3?
On the Artificial Analysis Intelligence Index, MiniMax M3.1 Flash scores 42.7 and GLM 5.3 scores 44.8, putting GLM 5.3 ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use MiniMax M3.1 Flash and GLM 5.3 at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see MiniMax M3.1 Flash and GLM 5.3 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to MiniMax M3.1 Flash and GLM 5.3 at the same time. Compare the answers side by side and keep the best one.