The AI arena is free today

Open Superagent

GLM-5.3 vs Phi-3.5-MoE-instruct

Comparing GLM-5.3 and Phi-3.5-MoE-instruct across benchmarks, pricing, and capabilities.

Zhipu AI · Microsoft · Updated for 2026

Which is better?

GLM-5.3 and Phi-3.5-MoE-instruct trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose GLM-5.3

  • you want the most recent training data — it shipped Aug 2026

Choose Phi-3.5-MoE-instruct

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

GLM-5.3
Zhipu AI
Phi-3.5-MoE-instruct
Microsoft
Benchmark wins
—
—
Input price
$1.40 / M
— / M
Output price
$4.40 / M
— / M
Context window
1,000,000
—
Released
Aug 2026
Aug 2024
License
Unknown
MIT

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5.3 and Phi-3.5-MoE-instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

693.0B diff

GLM-5.3 has 693.0B more parameters than Phi-3.5-MoE-instruct, making it 1155.0% larger.

Zhipu AI
GLM-5.3
753.0Bparameters
Microsoft
Phi-3.5-MoE-instruct
60.0Bparameters
753.0B
GLM-5.3
60.0B
Phi-3.5-MoE-instruct

Context Window

Maximum input and output token capacity

Only GLM-5.3 specifies input context (1,000,000 tokens). Only GLM-5.3 specifies output context (128,000 tokens).

Zhipu AI
GLM-5.3
Input1,000,000 tokens
Output128,000 tokens
Microsoft
Phi-3.5-MoE-instruct
Input- tokens
Output- tokens
Mon Aug 24 2026 • llm-stats.com

Release Timeline

When each model was launched

GLM-5.3 was released on 2026-08-14, while Phi-3.5-MoE-instruct was released on 2024-08-23.

GLM-5.3 is 24 months newer than Phi-3.5-MoE-instruct.

GLM-5.3

Aug 14, 2026

1 weeks ago

2.0yr newer
Phi-3.5-MoE-instruct

Aug 23, 2024

2.0 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GLM-5.3 and Phi-3.5-MoE-instruct side-by-side, then vote on the output you prefer.

GLM-5.3
✓ Preferred
Phi-3.5-MoE-instruct
Open in Playground

FAQ

Common questions about GLM-5.3 vs Phi-3.5-MoE-instruct.

Which is better, GLM-5.3 or Phi-3.5-MoE-instruct?

GLM-5.3 (Zhipu AI) and Phi-3.5-MoE-instruct (Microsoft) 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-5.3 compare to Phi-3.5-MoE-instruct in benchmarks?

GLM-5.3 scores Terminal-Bench 2.1: 88.2%, CyberGym: 84.5%, FrontierSWE: 78.1%, Toolathlon: 73.0%, DeepSWE 1.1: 66.9%. Phi-3.5-MoE-instruct scores ARC-C: 91.0%, OpenBookQA: 89.6%, GSM8k: 88.7%, PIQA: 88.6%, RULER: 87.1%.

What are the context window sizes for GLM-5.3 and Phi-3.5-MoE-instruct?

GLM-5.3 supports 1.0M tokens and Phi-3.5-MoE-instruct 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 and Phi-3.5-MoE-instruct?

Key differences include licensing (Unknown vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3 and Phi-3.5-MoE-instruct?

GLM-5.3 is developed by Zhipu AI and Phi-3.5-MoE-instruct is developed by Microsoft.

Related comparisons