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GLM-5.3 vs Sarvam-30B

Comparing GLM-5.3 and Sarvam-30B across benchmarks, pricing, and capabilities.

Zhipu AI · Sarvam AI · Updated for 2026

Which is better?

GLM-5.3 and Sarvam-30B 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 Sarvam-30B

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

At a glance

The differences that matter most.

GLM-5.3
Zhipu AI
Sarvam-30B
Sarvam AI
Benchmark wins
—
—
Input price
$1.40 / M
— / M
Output price
$4.40 / M
— / M
Context window
1,000,000
—
Released
Aug 2026
Mar 2026
License
Unknown
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5.3 and Sarvam-30Bdon'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

723.0B diff

GLM-5.3 has 723.0B more parameters than Sarvam-30B, making it 2410.0% larger.

Zhipu AI
GLM-5.3
753.0Bparameters
Sarvam AI
Sarvam-30B
30.0Bparameters
753.0B
GLM-5.3
30.0B
Sarvam-30B

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
Sarvam AI
Sarvam-30B
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 Sarvam-30B was released on 2026-03-06.

GLM-5.3 is 5 months newer than Sarvam-30B.

GLM-5.3

Aug 14, 2026

1 weeks ago

5mo newer
Sarvam-30B

Mar 6, 2026

5 months 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 Sarvam-30B side-by-side, then vote on the output you prefer.

GLM-5.3
✓ Preferred
Sarvam-30B
Open in Playground

FAQ

Common questions about GLM-5.3 vs Sarvam-30B.

Which is better, GLM-5.3 or Sarvam-30B?

GLM-5.3 (Zhipu AI) and Sarvam-30B (Sarvam AI) 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 Sarvam-30B 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%. Sarvam-30B scores MATH-500: 97.0%, AIME 2025: 96.7%, MBPP: 92.7%, HumanEval: 92.1%, MMLU: 85.1%.

What are the context window sizes for GLM-5.3 and Sarvam-30B?

GLM-5.3 supports 1.0M tokens and Sarvam-30B 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 Sarvam-30B?

Key differences include licensing (Unknown vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3 and Sarvam-30B?

GLM-5.3 is developed by Zhipu AI and Sarvam-30B is developed by Sarvam AI.

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