Model Comparison

GLM-5 vs Command R+

Comparing GLM-5 and Command R+ across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Command R+ don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Command R+ costs less

For input processing, GLM-5 ($1.00/1M tokens) is 4.0x more expensive than Command R+ ($0.25/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 3.2x more expensive than Command R+ ($1.00/1M tokens).

In conclusion, GLM-5 is more expensive than Command R+.*

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

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerUnknown Organization
Cohere
Command R+
Input tokens$0.25
Output tokens$1.00
Best providerCohere
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

640.0B diff

GLM-5 has 640.0B more parameters than Command R+, making it 615.4% larger.

Zhipu AI
GLM-5
744.0Bparameters
Cohere
Command R+
104.0Bparameters
744.0B
GLM-5
104.0B
Command R+

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to Command R+'s 128,000 tokens. Both models can generate responses up to 128,000 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Cohere
Command R+
Input128,000 tokens
Output128,000 tokens
Wed Apr 15 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Command R+ uses CC BY-NC.

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

GLM-5

MIT

Open weights

Command R+

CC BY-NC

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Command R+ was released on 2024-08-30.

GLM-5 is 18 months newer than Command R+.

GLM-5

Feb 11, 2026

2 months ago

1.5yr newer
Command R+

Aug 30, 2024

1.6 years 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

Provider Availability

GLM-5 is available from ZAI. Command R+ is available from Cohere, Bedrock.

GLM-5

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

Command R+

cohere logo
Cohere
Input Price:Input: $0.25/1MOutput Price:Output: $1.00/1M
bedrock logo
AWS Bedrock
Input Price:Input: $3.00/1MOutput Price:Output: $15.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Zhipu AI
Larger context window (200,000 tokens)
Cohere
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Cohere
Command R+

FAQ

Common questions about GLM-5 vs Command R+

GLM-5 (Zhipu AI) and Command R+ (Cohere) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
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%. Command R+ scores HellaSwag: 88.6%, Winogrande: 85.4%, MMLU: 75.7%, ARC-C: 71.0%, GSM8k: 70.7%.
Command R+ is 4.0x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via z. Command R+ costs $0.25/M input and $1.00/M output via cohere.
GLM-5 supports 200K tokens and Command R+ supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (200K vs 128K), input pricing ($1.00 vs $0.25/M), licensing (MIT vs CC BY-NC). See the full comparison above for benchmark-by-benchmark results.
GLM-5 is developed by Zhipu AI and Command R+ is developed by Cohere.