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GLM-5.3 vs Sarvam-105B

GLM-5.3 significantly outperforms across most benchmarks.

Zhipu AI · Sarvam AI · Updated for 2026

Which is better?

GLM-5.3 outperforms in 1 benchmarks (Humanity's Last Exam), while Sarvam-105B is better at 0 benchmarks. GLM-5.3 significantly outperforms across most benchmarks.

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

Choose GLM-5.3

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you want the most recent training data — it shipped Aug 2026

Choose Sarvam-105B

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

At a glance

The differences that matter most.

Benchmark wins
1 of 1
0 of 1
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

1 benchmarks

GLM-5.3 outperforms in 1 benchmarks (Humanity's Last Exam), while Sarvam-105B is better at 0 benchmarks.

GLM-5.3 significantly outperforms across most benchmarks.

Mon Aug 24 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

648.0B diff

GLM-5.3 has 648.0B more parameters than Sarvam-105B, making it 617.1% larger.

Zhipu AI
GLM-5.3
753.0Bparameters
Sarvam AI
Sarvam-105B
105.0Bparameters
753.0B
GLM-5.3
105.0B
Sarvam-105B

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-105B
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-105B was released on 2026-03-06.

GLM-5.3 is 5 months newer than Sarvam-105B.

GLM-5.3

Aug 14, 2026

1 weeks ago

5mo newer
Sarvam-105B

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-105B side-by-side, then vote on the output you prefer.

GLM-5.3
✓ Preferred
Sarvam-105B
Open in Playground

FAQ

Common questions about GLM-5.3 vs Sarvam-105B.

Which is better, GLM-5.3 or Sarvam-105B?

GLM-5.3 significantly outperforms across most benchmarks. GLM-5.3 is made by Zhipu AI and Sarvam-105B is made by Sarvam AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GLM-5.3 compare to Sarvam-105B 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-105B scores MATH-500: 98.6%, AIME 2025: 96.7%, MMLU: 90.6%, HMMT 2025: 85.8%, HMMT25: 85.8%.

What are the context window sizes for GLM-5.3 and Sarvam-105B?

GLM-5.3 supports 1.0M tokens and Sarvam-105B 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-105B?

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-105B?

GLM-5.3 is developed by Zhipu AI and Sarvam-105B is developed by Sarvam AI.