Official API pricing and token cost benchmarks for Glm 5 by Zhipu AI. Currently billed at $0.600 / 1M in and $2.08 / 1M out. Glm 5 is a balanced, cost-efficient standard model designed for general enterprise automation, structured data extraction, summarization, and daily developer workflows.
≈ $0.000600 per 1K tokens
3.5x higher than input
⚡ Saves 80% on cache hits
~270 standard pages
Standard per-token rate cards can feel abstract. Below is what calling Glm 5 actually costs across standardized enterprise workloads and engineering production loops.
How context length and prefix caching impact your bill at scale, and engineering strategies to optimize token throughput.
$0.122
1 full load of 202,752 tokens at standard input rates.
$0.024
Saves 80% on subsequent queries hitting pre-warmed cache.
3.5x
Output tokens cost 3.5x more than standard input tokens.
Because generation costs 3.5x more than input processing, using strict JSON schemas (Structured Outputs) to suppress conversational pleasantries directly lowers per-query cost by 40%–70%.
Prefix caching yields up to 80% savings. Always place static instructions, schemas, and reference code at the top of your prompt to maximize cache hit rates across agentic loops.
Current pricing specifications for Glm 5 via Deepinfra.
| Specification / Metric | Published Rate / Limit |
|---|---|
| Standard Input TokensPrompt, system instructions, and tool schemas | $0.600 / 1M tokens |
| Standard Output TokensGenerated text, reasoning steps, and tool calls | $2.08 / 1M tokens |
| Prompt Cache ReadCache hit on pre-loaded static prompt prefixes | $0.120 / 1M tokens (80% discount) |
| Prompt Cache Write / CreationInitial write to ephemeral prompt cache memory | Standard input rate |
| Context Window SizeMaximum combined input tokens per single request | 202,752 tokens (~270 pages) |
| Max Generation LengthMaximum output tokens generated per completion | 202,752 tokens |
| Batch API PricingAsynchronous workloads completed within 24 hours | 50% off standard token rates |
Comparable standard-tier models with their current per-token rates and cost differential.
| Model | Provider | Context | Input / 1M | Output / 1M | Input Cost Delta |
|---|---|---|---|---|---|
| Llama 4 Scout | Meta | 131K | $0.100 | $0.300 | -83% cheaper |
| Deepseek V3.2 | DeepSeek | 164K | $0.260 | $0.380 | -57% cheaper |
| Grok 4.3 | xAI | 1.0M | $1.25 | $2.50 | +108% higher |
| Qwen3.8 Max | Qwen | 1.0M | $1.65 | $4.99 | +175% higher |
Tier Positioning: Glm 5 is a balanced, cost-efficient standard model designed for general enterprise automation, structured data extraction, summarization, and daily developer workflows. Compared to other standard-tier models, Glm 5 offers a competitive rate card at $0.600 / 1M input and $2.08 / 1M output tokens.
Technical pricing details, caching rules, and budgeting considerations.
Glm 5 costs $0.600 per 1 million input tokens and $2.08 per 1 million output tokens. If prompt caching is active, cache reads cost $0.120 per 1M tokens.
Yes. Most major providers (including OpenAI, Anthropic, and Google) offer a 50% discount on standard token pricing for asynchronous Batch API jobs completed within a 24-hour turnaround window.
Prompt caching allows the provider to reuse pre-computed attention states from recurring prompt prefixes. Repeated prompt segments cost $0.120/1M tokens instead of $0.600/1M, saving ~80%.
Use our interactive AI Cost Calculator to input your exact daily request volume, average prompt token count, completion length, and prompt cache hit ratio. It generates precise cost forecasts across all models simultaneously.
Simulate real-world token consumption, model mixtures, and prompt cache savings with the DevFlow AI Cost Calculator.
