LLM Pricing Comparison
Input/output pricing per million tokens, performance scores, and estimated cost per 1M tasks.
| Model | Input Price | Output Price | Overall Score | Context | Est. Cost/1M Tasks | Key Strengths |
|---|---|---|---|---|---|---|
GLM-5 Zhipu AI | $0.5 | $0.5 | 8.5/10 | 128K | ~$0.80 | Ultra-low pricing • Enterprise ready • Good Chinese support |
DeepSeek V4 Pro DeepSeek | $0.435 | $0.87 | 9/10 | 1M | ~$0.85 | Best value performance • Hybrid thinking • 1M context |
MiniMax M2.5 MiniMax | $0.5 | $2 | 8.3/10 | 245K | ~$1.50 | Low cost • Multimodal support • Fast inference |
Kimi K3 Moonshot | $3 | $15 | 8.9/10 | 1M | ~$7.50 | Configurable reasoning • Native visual understanding • 1M context |
Gemini 3.1 Pro Preview Google | $2 | $12 | 8.4/10 | 1M | ~$7.00 | Prompt caching • Massive context • Good value |
Claude Opus 4.8 Anthropic | $5 | $25 | 9.4/10 | 1M | ~$15.00 | Best quality • Prompt caching • Complex tasks |
Real Cost Scenarios
Estimated cost per task at different complexity levels.
| Scenario | Tokens/Task | GLM-5 | DeepSeek | MiniMax | Claude |
|---|---|---|---|---|---|
| Simple classification | 500 | $0.0003 | $0.0003 | $0.0004 | $0.02 |
| Short code generation | 2,000 | $0.001 | $0.001 | $0.002 | $0.09 |
| Long document analysis | 10,000 | $0.005 | $0.006 | $0.01 | $0.45 |
| Complex multi-turn chat | 50,000 | $0.03 | $0.03 | $0.05 | $2.25 |
Cost Saving Strategies
Proven tactics to reduce your AI API spend.
Use prompt caching
Claude and Gemini offer caching that reduces costs 50-90% on repeated system prompts and context.
Up to 90% savingsRight-size your model
Use cheaper models for simple tasks. Reserve Claude/GPT-4 for complex reasoning and coding.
60-80% savingsOptimize token usage
Shorter prompts, structured output, and removing unnecessary context reduces costs significantly.
30-50% savingsBatch similar requests
Combine similar tasks into single API calls to reduce overhead and improve efficiency.
20-40% savingsMonitor and retry smarter
Track failure rates by model. Sometimes a more expensive model that works first try is cheaper.
10-30% savingsWhen to Use Which Model
Decision guide for balancing cost vs quality.
High-volume production API
Best balance of low cost, 1M context, and strong performance. Current listed pricing is $0.435/$0.87 per million tokens.
Enterprise on a budget
Lowest pricing at $0.50/$0.50 with solid 8.5/10 performance. Enterprise features included.
Need 1M context with configurable reasoning effort
Kimi lists a 1M-token context window and $3/$15 per million input/output pricing.
Long context + caching
Prompt caching can reduce costs 50-90% on repeated contexts. 1M context for large documents.
Quality matters more than cost
Best quality at 9.4/10. Use for critical tasks where accuracy justifies the premium.
Frequently Asked Questions
What is the cheapest LLM API in 2026?
+GLM-5 offers low pricing at $0.50 per million tokens for both input and output. DeepSeek V4 Pro is close at $0.435/$0.87 with stronger context and hybrid thinking. Both are dramatically cheaper than Claude Opus 4.8 ($5/$25) or GPT-5.5 ($5/$30).
How do I calculate my AI API costs?
+Cost = (input tokens × input price + output tokens × output price) / 1,000,000. Track your average tokens per task, multiply by your volume, and compare across models. Our cost scenarios table shows real examples.
Is it worth paying more for a better model?
+Sometimes yes. If a cheaper model requires 3 retries or produces unusable output, a more expensive model that works first try can be cheaper overall. Track success rates and retries, not just token costs.
What is prompt caching and how much does it save?
+Prompt caching stores processed prompt prefixes so repeated context doesn't need reprocessing. Claude and Gemini offer this. Savings range from 50-90% when your requests share common system prompts or documentation.
Should I use different models for different tasks?
+Yes. Route simple classification to GLM-5 or MiniMax, standard coding to DeepSeek, and complex architecture decisions to Claude. This "model routing" approach typically saves 40-60% vs using one premium model for everything.
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