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GLM-5.3-Flash vs MiniCPM-SALA

GLM-5.3-Flash leads the LLM Stats Score 51.6 to 12.7.

Zhipu AI · OpenBMB · Updated for 2026

Which is better?

GLM-5.3-Flash leads the overall LLM Stats Score 51.6 to 12.7, ranking #11 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GLM-5.3-Flash

  • overall performance matters — it scores 51.6 and ranks #11 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Aug 2026

Choose MiniCPM-SALA

  • you are already invested in the OpenBMB ecosystem

At a glance

The differences that matter most.

GLM-5.3-Flash
Zhipu AI
MiniCPM-SALA
OpenBMB
Core performance indexes
LLM Stats Score
51.6
#11
12.7
#230
Reasoning
50.3
#13
14.2
#214
Coding
37.8
#22
21.1
#80
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.15 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,048,576
—

Individual benchmarks

15 reported for GLM-5.3-Flash · 24 for MiniCPM-SALA

No common benchmarks found

GLM-5.3-Flash and MiniCPM-SALAdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

310.5B diff

GLM-5.3-Flash has 310.5B more parameters than MiniCPM-SALA, making it 3276.5% larger.

Zhipu AI
GLM-5.3-Flash
320.0Bparameters
OpenBMB
MiniCPM-SALA
9.5Bparameters
320.0B
GLM-5.3-Flash
9.5B
MiniCPM-SALA

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,048,576 tokens). Only GLM-5.3-Flash specifies output context (131,072 tokens).

Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
OpenBMB
MiniCPM-SALA
Input- tokens
Output- tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GLM-5.3-Flash supports multimodal inputs, whereas MiniCPM-SALA does not.

GLM-5.3-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5.3-Flash

Text
Images
Audio
Video

MiniCPM-SALA

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash is licensed under MIT, while MiniCPM-SALA uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

GLM-5.3-Flash

MIT

Open weights

MiniCPM-SALA

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while MiniCPM-SALA was released on 2026-02-11.

GLM-5.3-Flash is 7 months newer than MiniCPM-SALA.

GLM-5.3-Flash

Aug 26, 2026

2 days ago

6mo newer
MiniCPM-SALA

Feb 11, 2026

6 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GLM-5.3-Flash and MiniCPM-SALA side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
MiniCPM-SALA
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs MiniCPM-SALA.

Which is better, GLM-5.3-Flash or MiniCPM-SALA?

GLM-5.3-Flash leads the LLM Stats Score 51.6 to 12.7. GLM-5.3-Flash is made by Zhipu AI and MiniCPM-SALA is made by OpenBMB. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-5.3-Flash compare to MiniCPM-SALA in benchmarks?

GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%. MiniCPM-SALA scores HumanEval: 95.1%, RULER 64k: 92.7%, RULER 128k: 89.4%, MBPP: 89.1%, RULER 512K: 87.1%.

What are the context window sizes for GLM-5.3-Flash and MiniCPM-SALA?

GLM-5.3-Flash supports 1.0M tokens and MiniCPM-SALA supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-5.3-Flash and MiniCPM-SALA?

Key differences include LLM Stats Score (51.6 vs 12.7), multimodal support (yes vs no), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3-Flash and MiniCPM-SALA?

GLM-5.3-Flash is developed by Zhipu AI and MiniCPM-SALA is developed by OpenBMB.

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