GLM-5.3
Open WeightsDeveloped by Zhipu AI · Released 2026-02-18
What are the token costs and operational benchmarks for GLM-5.3?
Architectural Overview
Frontier foundation model developed by Zhipu AI featuring Dense Bilingual Transformer architecture.
Optimal Production Use Cases
Bilingual flagship foundation model optimized for cross-lingual reasoning, long-form structured analysis, and enterprise tool execution.
Interactive Monthly Token Economics & ROI Forecaster
Model your expected production workload across prompt (input) and completion (output) tokens with prompt caching economics.
Estimated Monthly Spend
$0.35/1M in · $1.00/1M out
Prompt Cache: $0.090/1M read · $0.35/1M write
$0.10/1M in · $0.35/1M out
Prompt Cache: $0.020/1M read · $0.10/1M write
Head-to-Head Comparisons Involving GLM-5.3
GLM-5.3 vs Claude 3.5 Haiku
GLM-5.3 is 56.2% cheaper for input tokens ($0.35 vs. $0.80 per 1M tokens) and $1.00 vs. $4.00 for output tokens (2.3x cost difference). In terms of operational performance, GLM-5.3 delivers faster response latency with 160ms TTFT (30ms faster than Claude 3.5 Haiku). GLM-5.3 leads coding benchmarks at 56.0% SWE-bench vs. 40.6% for Claude 3.5 Haiku.
GLM-5.3 vs Claude 3.5 Sonnet
GLM-5.3 is 88.3% cheaper for input tokens ($0.35 vs. $3.00 per 1M tokens) and $1.00 vs. $15.00 for output tokens (8.6x cost difference). In terms of operational performance, GLM-5.3 delivers faster response latency with 160ms TTFT (150ms faster than Claude 3.5 Sonnet). GLM-5.3 leads coding benchmarks at 56.0% SWE-bench vs. 49.0% for Claude 3.5 Sonnet.
GLM-5.3 vs Claude 3.7 Sonnet
GLM-5.3 is 88.3% cheaper for input tokens ($0.35 vs. $3.00 per 1M tokens) and $1.00 vs. $15.00 for output tokens (8.6x cost difference). In terms of operational performance, GLM-5.3 delivers faster response latency with 160ms TTFT (490ms faster than Claude 3.7 Sonnet). Claude 3.7 Sonnet leads coding benchmarks at 70.3% SWE-bench vs. 56.0% for GLM-5.3.
GLM-5.3 vs DeepSeek R1
GLM-5.3 is 36.4% cheaper for input tokens ($0.35 vs. $0.55 per 1M tokens) and $1.00 vs. $2.19 for output tokens (1.6x cost difference). In terms of operational performance, GLM-5.3 delivers faster response latency with 160ms TTFT (1640ms faster than DeepSeek-R1). GLM-5.3 leads coding benchmarks at 56.0% SWE-bench vs. 49.2% for DeepSeek-R1.
GLM-5.3 vs DeepSeek V3
DeepSeek V3 is 60.0% cheaper for input tokens ($0.14 vs. $0.35 per 1M tokens) and $0.28 vs. $1.00 for output tokens (2.5x cost difference). In terms of operational performance, GLM-5.3 delivers faster response latency with 160ms TTFT (250ms faster than DeepSeek V3). GLM-5.3 leads coding benchmarks at 56.0% SWE-bench vs. 42.0% for DeepSeek V3.
GLM-5.3 vs DeepSeek-V4 Flash Vision Exp
DeepSeek-V4 Flash Vision Exp is 60.0% cheaper for input tokens ($0.14 vs. $0.35 per 1M tokens) and $0.56 vs. $1.00 for output tokens (2.5x cost difference). In terms of operational performance, DeepSeek-V4 Flash Vision Exp delivers faster response latency with 140ms TTFT (20ms faster than GLM-5.3). DeepSeek-V4 Flash Vision Exp leads coding benchmarks at 64.2% SWE-bench vs. 56.0% for GLM-5.3.
GLM-5.3 vs Gemini 2.0 Flash
Gemini 2.0 Flash is 71.4% cheaper for input tokens ($0.10 vs. $0.35 per 1M tokens) and $0.40 vs. $1.00 for output tokens (3.5x cost difference). In terms of operational performance, GLM-5.3 delivers faster response latency with 160ms TTFT (60ms faster than Gemini 2.0 Flash). GLM-5.3 leads coding benchmarks at 56.0% SWE-bench vs. 28.0% for Gemini 2.0 Flash.
GLM-5.3 vs Gemini 2.5 Flash
Gemini 2.5 Flash is 14.3% cheaper for input tokens ($0.30 vs. $0.35 per 1M tokens) and $2.50 vs. $1.00 for output tokens (1.2x cost difference). In terms of operational performance, Gemini 2.5 Flash delivers faster response latency with 110ms TTFT (50ms faster than GLM-5.3). Gemini 2.5 Flash leads coding benchmarks at 58.0% SWE-bench vs. 56.0% for GLM-5.3.
GLM-5.3 vs Gemini 2.5 Pro
GLM-5.3 is 72.0% cheaper for input tokens ($0.35 vs. $1.25 per 1M tokens) and $1.00 vs. $10.00 for output tokens (3.6x cost difference). In terms of operational performance, GLM-5.3 delivers faster response latency with 160ms TTFT (190ms faster than Gemini 2.5 Pro). Gemini 2.5 Pro leads coding benchmarks at 65.0% SWE-bench vs. 56.0% for GLM-5.3.
GLM-5.3 vs GLM-5.3-Flash
GLM-5.3-Flash is 65.7% cheaper for input tokens ($0.12 vs. $0.35 per 1M tokens) and $0.40 vs. $1.00 for output tokens (2.9x cost difference). In terms of operational performance, GLM-5.3-Flash delivers faster response latency with 90ms TTFT (70ms faster than GLM-5.3). GLM-5.3 leads coding benchmarks at 56.0% SWE-bench vs. 52.8% for GLM-5.3-Flash.
GLM-5.3 vs GPT-4.5
**GLM-5.3 decisively outperforms GPT-4.5 across efficiency and software engineering capabilities at a fraction of the cost.** It is 99.5% cheaper, charging $0.35 input and $1.00 output per 1M tokens versus $75.00 and $150.00. Furthermore, GLM-5.3 delivers a 160ms TTFT (690ms faster) and leads coding benchmarks with 56.0% on SWE-bench compared to GPT-4.5's 38.0%.
GLM-5.3 vs GPT-4o
GLM-5.3 is 86.0% cheaper for input tokens ($0.35 vs. $2.50 per 1M tokens) and $1.00 vs. $10.00 for output tokens (7.1x cost difference). In terms of operational performance, GLM-5.3 delivers faster response latency with 160ms TTFT (120ms faster than GPT-4o). GLM-5.3 leads coding benchmarks at 56.0% SWE-bench vs. 48.0% for GPT-4o.
GLM-5.3 vs GPT-4o Mini
GPT-4o Mini is 57.1% cheaper for input tokens ($0.15 vs. $0.35 per 1M tokens) and $0.60 vs. $1.00 for output tokens (2.3x cost difference). In terms of operational performance, GLM-5.3 delivers faster response latency with 160ms TTFT (60ms faster than GPT-4o Mini). GLM-5.3 leads coding benchmarks at 56.0% SWE-bench vs. 41.0% for GPT-4o Mini.
GLM-5.3 vs Grok 3
GLM-5.3 is 88.3% cheaper for input tokens ($0.35 vs. $3.00 per 1M tokens) and $1.00 vs. $15.00 for output tokens (8.6x cost difference). In terms of operational performance, GLM-5.3 delivers faster response latency with 160ms TTFT (540ms faster than Grok 3). Grok 3 leads coding benchmarks at 65.4% SWE-bench vs. 56.0% for GLM-5.3.
GLM-5.3 vs Grok 3 Mini
Grok 3 Mini is 14.3% cheaper for input tokens ($0.30 vs. $0.35 per 1M tokens) and $1.20 vs. $1.00 for output tokens (1.2x cost difference). In terms of operational performance, Grok 3 Mini delivers faster response latency with 150ms TTFT (10ms faster than GLM-5.3). GLM-5.3 leads coding benchmarks at 56.0% SWE-bench vs. 54.0% for Grok 3 Mini.
GLM-5.3 vs Llama 3.3 70B Instruct
**Llama 3.3 70B Instruct offers a massive cost advantage, while GLM-5.3 dominates in speed and coding performance.** Llama 3.3 is 65.7% cheaper for inputs ($0.12 vs. $0.35/1M tokens) and outputs ($0.30 vs. $1.00/1M). However, GLM-5.3 delivers superior latency at 160ms TTFT (290ms faster) and leads coding benchmarks with 56.0% on SWE-bench versus 42.5%.
GLM-5.3 vs Mistral Large 2
**GLM-5.3 significantly outperforms Mistral Large 2 across cost efficiency, latency, and coding performance.** GLM-5.3 is 82.5% cheaper on inputs ($0.35 vs. $2.00 per 1M) and 5.7x cheaper on outputs ($1.00 vs. $6.00). It also delivers faster 160ms TTFT (360ms lower latency) while leading SWE-bench coding benchmarks at 56.0% compared to 40.0%.
GLM-5.3 vs Mistral Large 2 (2411)
GLM-5.3 is 82.5% cheaper for input tokens ($0.35 vs. $2.00 per 1M tokens) and $1.00 vs. $6.00 for output tokens (5.7x cost difference). In terms of operational performance, GLM-5.3 delivers faster response latency with 160ms TTFT (290ms faster than Mistral Large 2411). GLM-5.3 leads coding benchmarks at 56.0% SWE-bench vs. 35.7% for Mistral Large 2411.
GLM-5.3 vs o1
**GLM-5.3 outperforms o1 while delivering an overwhelming 42.9x cost advantage.** At $0.35 per million input tokens (97.7% cheaper) and $1.00 for outputs versus o1’s $60.00, it drastically slashes expenses. GLM-5.3 also dominates coding with a 56.0% SWE-bench score versus 48.9%, operating with a 160ms TTFT that is 2440ms faster than o1.
GLM-5.3 vs OpenAI o3-mini
**GLM-5.3 decisively outperforms OpenAI o3-mini across cost, speed, and coding capabilities.** At $0.35 versus $1.10 per 1M input tokens, GLM-5.3 is 68.2% cheaper, with output at $1.00 versus $4.40. It delivers a 160ms TTFT (1040ms faster) and leads coding benchmarks with 56.0% on SWE-bench compared to o3-mini's 49.3%.
GLM-5.3 vs Qwen 3.8 27B
Qwen 3.8 27B is 42.9% cheaper for input tokens ($0.20 vs. $0.35 per 1M tokens) and $0.60 vs. $1.00 for output tokens (1.7x cost difference). In terms of operational performance, Qwen 3.8 27B delivers faster response latency with 120ms TTFT (40ms faster than GLM-5.3). Qwen 3.8 27B leads coding benchmarks at 58.4% SWE-bench vs. 56.0% for GLM-5.3.
GLM-5.3 vs Qwen 3.8 Flash Next
Qwen 3.8 Flash Next is 71.4% cheaper for input tokens ($0.10 vs. $0.35 per 1M tokens) and $0.35 vs. $1.00 for output tokens (3.5x cost difference). In terms of operational performance, Qwen 3.8 Flash Next delivers faster response latency with 95ms TTFT (65ms faster than GLM-5.3). Qwen 3.8 Flash Next leads coding benchmarks at 61.0% SWE-bench vs. 56.0% for GLM-5.3.
Frequently Asked Questions & Query Fan-Out
How much does GLM-5.3 cost per 1M tokens?
GLM-5.3 costs $0.35 per million prompt (input) tokens and $1.00 per million completion (output) tokens.
What is the context window for GLM-5.3?
GLM-5.3 supports a maximum context window of 131,072 tokens, with a maximum single-generation output of 16,384 tokens.
What are the primary use cases for GLM-5.3?
Bilingual flagship foundation model optimized for cross-lingual reasoning, long-form structured analysis, and enterprise tool execution.