Model Comparison

GLM-5 vs MiMo-V2-Omni

GLM-5 significantly outperforms across most benchmarks. MiMo-V2-Omni is 1.9x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GLM-5 outperforms in 1 benchmarks (SWE-Bench Verified), while MiMo-V2-Omni is better at 0 benchmarks.

GLM-5 significantly outperforms across most benchmarks.

Fri Apr 03 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

MiMo-V2-Omni costs less

For input processing, GLM-5 ($1.00/1M tokens) is 2.5x more expensive than MiMo-V2-Omni ($0.40/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 1.6x more expensive than MiMo-V2-Omni ($2.00/1M tokens).

In conclusion, GLM-5 is more expensive than MiMo-V2-Omni.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Fri Apr 03 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerUnknown Organization
Xiaomi
MiMo-V2-Omni
Input tokens$0.40
Output tokens$2.00
Best providerXiaomi
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

MiMo-V2-Omni accepts 262,000 input tokens compared to GLM-5's 200,000 tokens. GLM-5 can generate longer responses up to 128,000 tokens, while MiMo-V2-Omni is limited to 16,384 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Xiaomi
MiMo-V2-Omni
Input262,000 tokens
Output16,384 tokens
Fri Apr 03 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

MiMo-V2-Omni supports multimodal inputs, whereas GLM-5 does not.

MiMo-V2-Omni can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5

Text
Images
Audio
Video

MiMo-V2-Omni

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while MiMo-V2-Omni uses a proprietary license.

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

GLM-5

MIT

Open weights

MiMo-V2-Omni

Proprietary

Closed source

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while MiMo-V2-Omni was released on 2026-03-18.

MiMo-V2-Omni is 1 month newer than GLM-5.

GLM-5

Feb 11, 2026

1 months ago

MiMo-V2-Omni

Mar 18, 2026

2 weeks ago

1mo newer

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

Provider Availability

GLM-5 is available from ZAI. MiMo-V2-Omni is available from Xiaomi.

GLM-5

z logo
Unknown Organization
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M

MiMo-V2-Omni

xiaomi logo
Xiaomi
Input Price:Input: $0.40/1MOutput Price:Output: $2.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Zhipu AI
Has open weights
Higher SWE-Bench Verified score (77.8% vs 74.8%)
Xiaomi
Larger context window (262,000 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Xiaomi
MiMo-V2-Omni

FAQ

Common questions about GLM-5 vs MiMo-V2-Omni

GLM-5 significantly outperforms across most benchmarks. GLM-5 is made by Zhipu AI and MiMo-V2-Omni is made by Xiaomi. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. MiMo-V2-Omni scores PinchBench: 81.2%, SWE-Bench Verified: 74.8%, Claw-Eval: 54.8%, MM-BrowserComp: 52.0%, OmniGAIA: 49.8%.
MiMo-V2-Omni is 2.5x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via z. MiMo-V2-Omni costs $0.40/M input and $2.00/M output via xiaomi.
GLM-5 supports 200K tokens and MiMo-V2-Omni supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (200K vs 262K), input pricing ($1.00 vs $0.40/M), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.
GLM-5 is developed by Zhipu AI and MiMo-V2-Omni is developed by Xiaomi.