Model Comparison

GLM-5 vs Llama 3.1 70B InstructWhich is better in 2026?

Comparing GLM-5 and Llama 3.1 70B Instruct across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs Llama 3.1 70B Instruct — which is better?

GLM-5 (by Zhipu AI) and Llama 3.1 70B Instruct (by Meta) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

On price, Llama 3.1 70B Instruct is roughly 7.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GLM-5 also accepts a larger context window (200,000 input tokens), making it the stronger choice for long documents and large codebases.

Choose GLM-5 if…

you process long inputs — it offers a 200,000 token context window
you want the most recent training data — it shipped Feb 2026

Choose Llama 3.1 70B Instruct if…

cost matters — it's about 7.8x cheaper per token

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Llama 3.1 70B Instruct 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

Llama 3.1 70B Instruct costs less

For input processing, GLM-5 ($1.00/1M tokens) is 5.0x more expensive than Llama 3.1 70B Instruct ($0.20/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 16.0x more expensive than Llama 3.1 70B Instruct ($0.20/1M tokens).

In conclusion, GLM-5 is more expensive than Llama 3.1 70B Instruct.*

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

Lowest available price from all providers

Sat Jun 06 2026 • llm-stats.com

GLM-5

Input tokens$1.00

Output tokens$3.20

Best providerFriendliAI

Llama 3.1 70B Instruct

Input tokens$0.20

Output tokens$0.20

Best providerLambda

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

674.0B diff

GLM-5 has 674.0B more parameters than Llama 3.1 70B Instruct, making it 962.9% larger.

GLM-5

744.0Bparameters

Llama 3.1 70B Instruct

70.0Bparameters

744.0B

GLM-5

70.0B

Llama 3.1 70B Instruct

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to Llama 3.1 70B Instruct's 128,000 tokens. Both models can generate responses up to 128,000 tokens.

GLM-5

Input200,000 tokens

Output128,000 tokens

Llama 3.1 70B Instruct

Input128,000 tokens

Output128,000 tokens

Sat Jun 06 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Llama 3.1 70B Instruct uses Llama 3.1 Community License.

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

GLM-5

MIT

Open weights

Llama 3.1 70B Instruct

Llama 3.1 Community License

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Llama 3.1 70B Instruct was released on 2024-07-23.

GLM-5 is 19 months newer than Llama 3.1 70B Instruct.

GLM-5

Feb 11, 2026

3 months ago

1.6yr newer

Llama 3.1 70B Instruct

Jul 23, 2024

1.9 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 FriendliAI, ZAI. Llama 3.1 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Cerebras, Together, Fireworks, Bedrock, Sambanova.

GLM-5

FriendliAI

Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M

Unknown Organization

Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M

Llama 3.1 70B Instruct

Lambda

Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M

Deepinfra

Input Price:Input: $0.35/1MOutput Price:Output: $0.40/1M

Hyperbolic

Input Price:Input: $0.40/1MOutput Price:Output: $0.40/1M

Groq

Input Price:Input: $0.59/1MOutput Price:Output: $0.78/1M

Cerebras

Input Price:Input: $0.60/1MOutput Price:Output: $0.60/1M

Together

Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M

Fireworks

Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M

AWS Bedrock

Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M

Sambanova

Input Price:Input: $5.00/1MOutput Price:Output: $10.00/1M

* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

GLM-5

View details

Zhipu AI

Larger context window (200,000 tokens)

Detailed Comparison

AI Model Comparison Table
Feature	GLM-5	Llama 3.1 70B Instruct

FAQ

Common questions about GLM-5 vs Llama 3.1 70B Instruct.

Which is better, GLM-5 or Llama 3.1 70B Instruct?

GLM-5 (Zhipu AI) and Llama 3.1 70B Instruct (Meta) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does GLM-5 compare to Llama 3.1 70B Instruct in benchmarks?

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%. Llama 3.1 70B Instruct scores GSM-8K (CoT): 95.1%, ARC-C: 94.8%, API-Bank: 90.0%, IFEval: 87.5%, Multilingual MGSM (CoT): 86.9%.

Is GLM-5 cheaper than Llama 3.1 70B Instruct?

Llama 3.1 70B Instruct is 5.0x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via friendli. Llama 3.1 70B Instruct costs $0.20/M input and $0.20/M output via lambda.

What are the context window sizes for GLM-5 and Llama 3.1 70B Instruct?

GLM-5 supports 200K tokens and Llama 3.1 70B Instruct supports 128K 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 and Llama 3.1 70B Instruct?

Key differences include context window (200K vs 128K), input pricing ($1.00 vs $0.20/M), licensing (MIT vs Llama 3.1 Community License). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Llama 3.1 70B Instruct?

GLM-5 is developed by Zhipu AI and Llama 3.1 70B Instruct is developed by Meta.

GLM-5 vs Llama 3.1 70B InstructWhich is better in 2026?

Verdict: GLM-5 vs Llama 3.1 70B Instruct — which is better?

Choose GLM-5 if…

Choose Llama 3.1 70B Instruct if…

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

License

Release Timeline

Knowledge Cutoff

Provider Availability

GLM-5

Llama 3.1 70B Instruct

Outputs Comparison

Key Takeaways

GLM-5

Llama 3.1 70B Instruct

Detailed Comparison

FAQ

Which is better, GLM-5 or Llama 3.1 70B Instruct?

How does GLM-5 compare to Llama 3.1 70B Instruct in benchmarks?

Is GLM-5 cheaper than Llama 3.1 70B Instruct?

What are the context window sizes for GLM-5 and Llama 3.1 70B Instruct?

What are the main differences between GLM-5 and Llama 3.1 70B Instruct?

Who makes GLM-5 and Llama 3.1 70B Instruct?

More GLM-5 comparisons

More Llama 3.1 70B Instruct comparisons

GLM-5 vs Llama 3.1 70B InstructWhich is better in 2026?

Verdict: GLM-5 vs Llama 3.1 70B Instruct — which is better?

Choose GLM-5 if…

Choose Llama 3.1 70B Instruct if…

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

License

Release Timeline

Knowledge Cutoff

Provider Availability

GLM-5

Llama 3.1 70B Instruct

Outputs Comparison

Key Takeaways

GLM-5

Llama 3.1 70B Instruct

Detailed Comparison

Which is better, GLM-5 or Llama 3.1 70B Instruct?

How does GLM-5 compare to Llama 3.1 70B Instruct in benchmarks?

Is GLM-5 cheaper than Llama 3.1 70B Instruct?

What are the context window sizes for GLM-5 and Llama 3.1 70B Instruct?

What are the main differences between GLM-5 and Llama 3.1 70B Instruct?

Who makes GLM-5 and Llama 3.1 70B Instruct?

Related comparisons

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