GLM-5.3
Open WeightsDeveloped by Zhipu AI · Dense Bilingual Transformer · Modalities: Text, Code · Released 2026-02-18
What are the token costs and operational benchmarks for GLM-5.3?
Verified Capability Benchmarks
Composite Intelligence: 70.7/100Architectural & Production Profile
Zhipu AI's bilingual flagship foundation model tuned for cross-lingual reasoning, structured function calling, and agentic execution.
Bilingual flagship foundation model optimized for cross-lingual reasoning, long-form structured analysis, and enterprise tool execution.
- Architecture
- Dense Bilingual Transformer
- Modalities
- Text, Code
- Max Output Tokens
- 16,384 tokens
- Blended Rate (3:1)
- $0.512 / 1M
Verified Cloud Inference Endpoints Hosting GLM-5.3
Compare latency, streaming speed, and token pricing across cloud API providers.
| Inference Provider | Role | Input / 1M | Output / 1M | Avg TTFT | Throughput |
|---|---|---|---|---|---|
| Zhipu AI BigModel Platform → | Primary Host | $0.35 | $1.00 | 160ms | 120 tok/s |
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Estimated Monthly Spend
$0.35/1M in · $1.00/1M out
Prompt Cache: $0.090/1M read · $0.35/1M write
$2.00/1M in · $10.00/1M out
Prompt Cache: $0.100/1M read · $0.50/1M write
Head-to-Head Comparisons Involving GLM-5.3 (36)
GLM-5.3 vs Gemini 4 Argon
GLM-5.3 is 82.5% cheaper for input tokens ($0.35 vs. $2.00 per 1M tokens) and $1.00 vs. $10.00 for output tokens (5.7x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (690ms faster than Gemini 4 Argon) with 120 vs. 115 tok/s throughput. Gemini 4 Argon leads coding evaluations at 84.5% SWE-bench Verified vs. 56.0% for GLM-5.3 and 93.8% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs Claude 4.5 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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (220ms faster than Claude 4.5 Sonnet) with 120 vs. 84 tok/s throughput. Claude 4.5 Sonnet leads coding evaluations at 75.8% SWE-bench Verified vs. 56.0% for GLM-5.3 and 84.2% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs Claude Opus 5.5
GLM-5.3 is 91.2% cheaper for input tokens ($0.35 vs. $4.00 per 1M tokens) and $1.00 vs. $20.00 for output tokens (11.4x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (520ms faster than Claude Opus 5.5) with 120 vs. 95 tok/s throughput. Claude Opus 5.5 leads coding evaluations at 89.9% SWE-bench Verified vs. 56.0% for GLM-5.3 and 93.2% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs Gemini 3.8 Flash
Gemini 3.8 Flash is 28.6% cheaper for input tokens ($0.25 vs. $0.35 per 1M tokens) and $1.50 vs. $1.00 for output tokens (1.4x cost advantage). In terms of operational performance, Gemini 3.8 Flash delivers lower response latency at 105ms TTFT (55ms faster than GLM-5.3) with 210 vs. 120 tok/s throughput. Gemini 3.8 Flash leads coding evaluations at 68.5% SWE-bench Verified vs. 56.0% for GLM-5.3 and 79.2% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs GPT-5
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (180ms faster than GPT-5) with 120 vs. 105 tok/s throughput. GPT-5 leads coding evaluations at 74.9% SWE-bench Verified vs. 56.0% for GLM-5.3 and 85.4% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs GPT-6 Astra
GLM-5.3 is 96.5% cheaper for input tokens ($0.35 vs. $10.00 per 1M tokens) and $1.00 vs. $50.00 for output tokens (28.6x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (580ms faster than GPT-6 Astra) with 120 vs. 74 tok/s throughput. GPT-6 Astra leads coding evaluations at 75.7% SWE-bench Verified vs. 56.0% for GLM-5.3 and 96.0% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs DeepSeek V4 Pro
GLM-5.3 is 73.5% cheaper for input tokens ($0.35 vs. $1.32 per 1M tokens) and $1.00 vs. $3.96 for output tokens (3.8x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (360ms faster than DeepSeek V4 Pro) with 120 vs. 78 tok/s throughput. DeepSeek V4 Pro leads coding evaluations at 80.6% SWE-bench Verified vs. 56.0% for GLM-5.3 and 90.1% vs. 67.0% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (1290ms faster than DeepSeek R1) with 120 vs. 58 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 49.2% for DeepSeek R1 and 67.0% vs. 71.5% on GPQA Diamond.
GLM-5.3 vs DeepSeek V4 Flash Vision (Exp)
DeepSeek V4 Flash Vision (Exp) is 37.1% cheaper for input tokens ($0.22 vs. $0.35 per 1M tokens) and $0.65 vs. $1.00 for output tokens (1.6x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (150ms faster than DeepSeek V4 Flash Vision (Exp)) with 120 vs. 165 tok/s throughput. DeepSeek V4 Flash Vision (Exp) leads coding evaluations at 77.4% SWE-bench Verified vs. 56.0% for GLM-5.3 and 91.3% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs OpenAI o3
GLM-5.3 is 82.5% cheaper for input tokens ($0.35 vs. $2.00 per 1M tokens) and $1.00 vs. $8.00 for output tokens (5.7x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (990ms faster than OpenAI o3) with 120 vs. 82 tok/s throughput. OpenAI o3 leads coding evaluations at 71.7% SWE-bench Verified vs. 56.0% for GLM-5.3 and 87.7% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs Claude 4 Opus
GLM-5.3 is 97.7% cheaper for input tokens ($0.35 vs. $15.00 per 1M tokens) and $1.00 vs. $75.00 for output tokens (42.9x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (760ms faster than Claude 4 Opus) with 120 vs. 46 tok/s throughput. Claude 4 Opus leads coding evaluations at 77.2% SWE-bench Verified vs. 56.0% for GLM-5.3 and 87.1% vs. 67.0% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (380ms faster than Claude 3.7 Sonnet) with 120 vs. 72 tok/s throughput. Claude 3.7 Sonnet leads coding evaluations at 70.3% SWE-bench Verified vs. 56.0% for GLM-5.3 and 78.5% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs Gemini 3.1 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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (260ms faster than Gemini 3.1 Pro) with 120 vs. 98 tok/s throughput. Gemini 3.1 Pro leads coding evaluations at 71.8% SWE-bench Verified vs. 56.0% for GLM-5.3 and 82.4% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs Grok 4
GLM-5.3 is 86.0% cheaper for input tokens ($0.35 vs. $2.50 per 1M tokens) and $1.00 vs. $12.50 for output tokens (7.1x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (320ms faster than Grok 4) with 120 vs. 95 tok/s throughput. Grok 4 leads coding evaluations at 73.2% SWE-bench Verified vs. 56.0% for GLM-5.3 and 86.2% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs Llama 4 Maverick
Llama 4 Maverick 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 advantage). In terms of operational performance, Llama 4 Maverick delivers lower response latency at 135ms TTFT (25ms faster than GLM-5.3) with 175 vs. 120 tok/s throughput. Llama 4 Maverick leads coding evaluations at 62.4% SWE-bench Verified vs. 56.0% for GLM-5.3 and 73.8% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs Qwen 3.8 Flash Next
Qwen 3.8 Flash Next is 54.3% cheaper for input tokens ($0.16 vs. $0.35 per 1M tokens) and $0.47 vs. $1.00 for output tokens (2.2x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (120ms faster than Qwen 3.8 Flash Next) with 120 vs. 185 tok/s throughput. Qwen 3.8 Flash Next leads coding evaluations at 81.0% SWE-bench Verified vs. 56.0% for GLM-5.3 and 91.7% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs Gemini 3.5 Flash-Lite
Gemini 3.5 Flash-Lite is 78.6% cheaper for input tokens ($0.07 vs. $0.35 per 1M tokens) and $0.30 vs. $1.00 for output tokens (4.7x cost advantage). In terms of operational performance, Gemini 3.5 Flash-Lite delivers lower response latency at 78ms TTFT (82ms faster than GLM-5.3) with 265 vs. 120 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 55.4% for Gemini 3.5 Flash-Lite and 67.0% vs. 68.4% on GPQA Diamond.
GLM-5.3 vs OpenAI o4-mini
GLM-5.3 is 68.2% cheaper for input tokens ($0.35 vs. $1.10 per 1M tokens) and $1.00 vs. $4.40 for output tokens (3.1x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (520ms faster than OpenAI o4-mini) with 120 vs. 125 tok/s throughput. OpenAI o4-mini leads coding evaluations at 68.1% SWE-bench Verified vs. 56.0% for GLM-5.3 and 81.4% vs. 67.0% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (250ms faster than DeepSeek V3) with 120 vs. 78 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 67.0% vs. 59.1% on GPQA Diamond.
GLM-5.3 vs Gemma 4 31B IT
Gemma 4 31B IT is 65.7% cheaper for input tokens ($0.12 vs. $0.35 per 1M tokens) and $0.36 vs. $1.00 for output tokens (2.9x cost advantage). In terms of operational performance, Gemma 4 31B IT delivers lower response latency at 115ms TTFT (45ms faster than GLM-5.3) with 155 vs. 120 tok/s throughput. Gemma 4 31B IT leads coding evaluations at 59.2% SWE-bench Verified vs. 56.0% for GLM-5.3 and 71.2% vs. 67.0% on GPQA Diamond.
GLM-5.3 vs OpenAI o3-mini
GLM-5.3 is 68.2% cheaper for input tokens ($0.35 vs. $1.10 per 1M tokens) and $1.00 vs. $4.40 for output tokens (3.1x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (790ms faster than OpenAI o3-mini) with 120 vs. 98 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 49.3% for OpenAI o3-mini and 67.0% vs. 79.7% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (30ms faster than Claude 3.5 Haiku) with 120 vs. 130 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 40.6% for Claude 3.5 Haiku and 67.0% vs. 41.6% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (150ms faster than Claude 3.5 Sonnet) with 120 vs. 80 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 49.0% for Claude 3.5 Sonnet and 67.0% vs. 59.4% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (120ms faster than Gemini 2.0 Flash) with 120 vs. 185 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 51.8% for Gemini 2.0 Flash and 67.0% vs. 63.6% on GPQA Diamond.
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 advantage). In terms of operational performance, Gemini 2.5 Flash delivers lower response latency at 110ms TTFT (50ms faster than GLM-5.3) with 180 vs. 120 tok/s throughput. Gemini 2.5 Flash leads coding evaluations at 58.0% SWE-bench Verified vs. 56.0% for GLM-5.3 and 70.5% vs. 67.0% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (540ms faster than Gemini 2.5 Pro) with 120 vs. 80 tok/s throughput. Gemini 2.5 Pro leads coding evaluations at 63.8% SWE-bench Verified vs. 56.0% for GLM-5.3 and 74.0% vs. 67.0% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3-Flash delivers lower response latency at 90ms TTFT (70ms faster than GLM-5.3) with 175 vs. 120 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 52.8% for GLM-5.3-Flash and 67.0% vs. 63.5% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (120ms faster than GPT-4o) with 120 vs. 100 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 48.0% for GPT-4o and 67.0% vs. 53.6% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (60ms faster than GPT-4o Mini) with 120 vs. 140 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 41.0% for GPT-4o Mini and 67.0% vs. 40.2% on GPQA Diamond.
GLM-5.3 vs GPT-6.1 Sol
GLM-5.3 is 82.5% cheaper for input tokens ($0.35 vs. $2.00 per 1M tokens) and $1.00 vs. $10.00 for output tokens (5.7x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (360ms faster than GPT-6.1 Sol) with 120 vs. 135 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 56.0% for GLM-5.3 and 92.4% vs. 67.0% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (460ms faster than Grok 3) with 120 vs. 88 tok/s throughput. Grok 3 leads coding evaluations at 65.8% SWE-bench Verified vs. 56.0% for GLM-5.3 and 84.6% vs. 67.0% on GPQA Diamond.
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 advantage). In terms of operational performance, Grok 3 Mini delivers lower response latency at 150ms TTFT (10ms faster than GLM-5.3) with 160 vs. 120 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 54.0% for Grok 3 Mini and 67.0% vs. 68.0% on GPQA Diamond.
GLM-5.3 vs Llama 3.3 70B Instruct
Llama 3.3 70B Instruct is 65.7% cheaper for input tokens ($0.12 vs. $0.35 per 1M tokens) and $0.30 vs. $1.00 for output tokens (2.9x cost advantage). In terms of operational performance, Llama 3.3 70B Instruct delivers lower response latency at 145ms TTFT (15ms faster than GLM-5.3) with 165 vs. 120 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 42.5% for Llama 3.3 70B Instruct and 67.0% vs. 55.6% on GPQA Diamond.
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 advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (220ms faster than Mistral Large 2 (2411)) with 120 vs. 75 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 67.0% vs. 54.2% on GPQA Diamond.
GLM-5.3 vs o1
GLM-5.3 is 97.7% cheaper for input tokens ($0.35 vs. $15.00 per 1M tokens) and $1.00 vs. $60.00 for output tokens (42.9x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (2440ms faster than o1) with 120 vs. 48 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 48.9% for o1 and 67.0% vs. 78.0% on GPQA Diamond.
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 advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (40ms faster than GLM-5.3) with 140 vs. 120 tok/s throughput. Qwen 3.8 27B leads coding evaluations at 58.4% SWE-bench Verified vs. 56.0% for GLM-5.3 and 68.0% vs. 67.0% on GPQA Diamond.
Frequently Asked Questions & Query Fan-Out
How much does GLM-5.3 cost per 1M tokens including prompt caching?
GLM-5.3 costs $0.35 per million input tokens and $1.00 per million output tokens. Cached input reads cost $0.090 per 1M tokens, reducing repeated context costs by 74%.
What are GLM-5.3's coding and reasoning benchmark scores?
GLM-5.3 achieves 56% on SWE-bench Verified, 91.5% on HumanEval coding, 67% on GPQA Diamond graduate-level science, 80.5% on MMLU-Pro, and 88% on MATH-500, earning an overall Inference Value Ratio (IVR) of 69.9/100.
What is the context window, TTFT latency, and token throughput of GLM-5.3?
GLM-5.3 supports a 131,072 token context window (16,384 max output tokens) and operates at 160ms average Time to First Token (TTFT) with 120 tokens/sec output streaming throughput.
What are the primary production use cases for GLM-5.3?
Bilingual flagship foundation model optimized for cross-lingual reasoning, long-form structured analysis, and enterprise tool execution.