AI model comparison
MiMo-V2.6-Pro vs GLM 5.3 FlashX
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Xiaomi
MiMo-V2.6-Pro
MiMo-V2.6-Pro is the flagship foundation model developed by Xiaomi.
- Input / 1M
- $0.44
- Output / 1M
- $0.87
- Context
- 1.05M
Z.ai
GLM 5.3 FlashX
GLM-5.3-FlashX is the high-speed variant of Z.ai's GLM-5.3-Flash, a native multimodal model delivering inference speeds of up to 200 tokens/s.
- Input / 1M
- $0.37
- Output / 1M
- $1.25
- Context
- 1.05M
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
MiMo-V2.6-Pro
1.0x cheaper for a typical chat
Higher intelligence score
Tie
Not enough benchmark data
Larger context window
MiMo-V2.6-Pro
1.05M vs 1.05M tokens
Newer release
MiMo-V2.6-Pro
Released September 21, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
MiMo-V2.6-Pro vs GLM 5.3 FlashX API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.44 | $0.37 |
| Output tokensPer 1M tokens | $0.87 | $1.25 |
| Cached input (read)Per 1M tokens | $0.00 | $0.09 |
| 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 | 1.05M tokens | 1.05M tokens |
| Max output | 131K tokens | 131K tokens |
| Input types | Audio, Image, Text, Video | Image, Text, Video |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Max, High, Low |
| Default reasoning effort | Not available | Max |
| Release date | September 21, 2026 | September 18, 2026 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Not supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Not supported |
| Deterministic seed | Supported | Not supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
- MiMo-V2.6-Pro vs DeepSeek V4.1 Flash
- MiMo-V2.6-Pro vs Muse Spark 1.3
- MiMo-V2.6-Pro vs GLM 5.3 Flash
- MiMo-V2.6-Pro vs MiMo-V2.6-Flash
- MiMo-V2.6-Pro vs GPT-5.6 Sol
- MiMo-V2.6-Pro vs Grok 4.7
- MiMo-V2.6-Pro vs GPT-6 Luna
- MiMo-V2.6-Pro vs Qwen3.8 Max (0902)
- MiMo-V2.6-Pro vs GLM 5.3
- MiMo-V2.6-Pro vs Claude Haiku 5.5
- MiMo-V2.6-Pro vs Ling 3.1 Flash
Our take
MiMo-V2.6-Pro is 1.0x cheaper for a typical chat. MiMo-V2.6-Pro has the larger context window (1.05M vs 1.05M 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 MiMo-V2.6-Pro or GLM 5.3 FlashX cheaper?
MiMo-V2.6-Pro is cheaper for a typical chat (2K input tokens and 500 output tokens). MiMo-V2.6-Pro costs $0.44 per 1M input tokens and $0.87 per 1M output tokens, while GLM 5.3 FlashX costs $0.37 per 1M input tokens and $1.25 per 1M output tokens.
Which has a bigger context window, MiMo-V2.6-Pro or GLM 5.3 FlashX?
MiMo-V2.6-Pro supports up to 1.05M tokens of context, compared with 1.05M for GLM 5.3 FlashX.
Can I use MiMo-V2.6-Pro and GLM 5.3 FlashX at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see MiMo-V2.6-Pro and GLM 5.3 FlashX answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to MiMo-V2.6-Pro and GLM 5.3 FlashX at the same time. Compare the answers side by side and keep the best one.