Model Comparison

GLM-5 vs DeepSeek-V3.1Which is better in 2026?

GLM-5 significantly outperforms across most benchmarks. DeepSeek-V3.1 is 3.4x cheaper per token.

Verdict: GLM-5 vs DeepSeek-V3.1 — which is better?

GLM-5 (by Zhipu AI) and DeepSeek-V3.1 (by DeepSeek) 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.

GLM-5 outperforms in 2 benchmarks (BrowseComp, SWE-Bench Verified), while DeepSeek-V3.1 is better at 0 benchmarks. GLM-5 significantly outperforms across most benchmarks.

On price, DeepSeek-V3.1 is roughly 3.4x 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 want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • you process long inputs — it offers a 200,000 token context window
  • you want the most recent training data — it shipped Feb 2026

Choose DeepSeek-V3.1 if…

  • cost matters — it's about 3.4x cheaper per token

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

GLM-5 outperforms in 2 benchmarks (BrowseComp, SWE-Bench Verified), while DeepSeek-V3.1 is better at 0 benchmarks.

GLM-5 significantly outperforms across most benchmarks.

Tue Jul 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.1 costs less

For input processing, GLM-5 ($1.00/1M tokens) is 3.7x more expensive than DeepSeek-V3.1 ($0.27/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 3.2x more expensive than DeepSeek-V3.1 ($1.00/1M tokens).

In conclusion, GLM-5 is more expensive than DeepSeek-V3.1.*

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

Lowest available price from all providers
Tue Jul 14 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerFriendliAI
DeepSeek
DeepSeek-V3.1
Input tokens$0.27
Output tokens$1.00
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

73.0B diff

GLM-5 has 73.0B more parameters than DeepSeek-V3.1, making it 10.9% larger.

Zhipu AI
GLM-5
744.0Bparameters
DeepSeek
DeepSeek-V3.1
671.0Bparameters
744.0B
GLM-5
671.0B
DeepSeek-V3.1

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to DeepSeek-V3.1's 163,840 tokens. DeepSeek-V3.1 can generate longer responses up to 163,840 tokens, while GLM-5 is limited to 128,000 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Tue Jul 14 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

GLM-5

MIT

Open weights

DeepSeek-V3.1

MIT

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while DeepSeek-V3.1 was released on 2025-01-10.

GLM-5 is 13 months newer than DeepSeek-V3.1.

GLM-5

Feb 11, 2026

5 months ago

1.1yr newer
DeepSeek-V3.1

Jan 10, 2025

1.5 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. DeepSeek-V3.1 is available from DeepInfra, Novita.

GLM-5

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

DeepSeek-V3.1

deepinfra logo
Deepinfra
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M
novita logo
Novita
Input Price:Input: $0.27/1MOutput Price:Output: $1.00/1M
* 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)
Higher BrowseComp score (75.9% vs 30.0%)
Higher SWE-Bench Verified score (77.8% vs 66.0%)
DeepSeek
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against GLM-5 and DeepSeek-V3.1 side-by-side, then vote on the output you prefer.

GLM-5
✓ Preferred
DeepSeek-V3.1
Open in Playground
AI Model Comparison Table
Feature
Zhipu AI
GLM-5
DeepSeek
DeepSeek-V3.1

FAQ

Common questions about GLM-5 vs DeepSeek-V3.1.

Which is better, GLM-5 or DeepSeek-V3.1?

GLM-5 significantly outperforms across most benchmarks. GLM-5 is made by Zhipu AI and DeepSeek-V3.1 is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GLM-5 compare to DeepSeek-V3.1 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%. DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%.

Is GLM-5 cheaper than DeepSeek-V3.1?

DeepSeek-V3.1 is 3.7x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via friendli. DeepSeek-V3.1 costs $0.27/M input and $1.00/M output via deepinfra.

What are the context window sizes for GLM-5 and DeepSeek-V3.1?

GLM-5 supports 200K tokens and DeepSeek-V3.1 supports 164K 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 DeepSeek-V3.1?

Key differences include context window (200K vs 164K), input pricing ($1.00 vs $0.27/M). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and DeepSeek-V3.1?

GLM-5 is developed by Zhipu AI and DeepSeek-V3.1 is developed by DeepSeek.

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