The Price War
The LLM API market in 2026 is experiencing a genuine price war. Over the past year, inference costs have dropped 2-5x depending on the provider. Letβs look at how much the main models cost today and how to choose the best option.
Price Table (March 2026)
Flagship Models
| Model |
Input ($/1M) |
Output ($/1M) |
Cached Input |
Context |
| GPT-5.3 |
$8.00 |
$24.00 |
$2.00 |
128K |
| Claude Opus 4.6 |
$15.00 |
$75.00 |
$3.75 |
200K |
| Claude Sonnet 4.6 |
$3.00 |
$15.00 |
$0.75 |
256K |
| Gemini 3.1 Pro |
$3.50 |
$10.50 |
$0.88 |
1M |
| DeepSeek V3 |
$0.27 |
$1.10 |
$0.07 |
128K |
| Qwen 3 72B |
$0.40 |
$1.20 |
β |
128K |
Lightweight Models
| Model |
Input ($/1M) |
Output ($/1M) |
Context |
| GPT-5.3 Mini |
$0.40 |
$1.60 |
128K |
| Claude Haiku 3.5 |
$0.80 |
$4.00 |
200K |
| Gemini 3.1 Flash |
$0.15 |
$0.60 |
1M |
| DeepSeek V3 Lite |
$0.07 |
$0.28 |
64K |
| Qwen 3 7B |
$0.05 |
$0.15 |
32K |
Reasoning Models
| Model |
Input ($/1M) |
Output ($/1M) |
| o3 |
$10.00 |
$40.00 |
| o4-mini |
$1.10 |
$4.40 |
| DeepSeek R1 |
$0.55 |
$2.19 |
| Claude Sonnet 4.6 (extended) |
$3.00 |
$15.00 |
What It Costs in Practice
Scenario 1: Analyzing a Single Financial Report
- Document size: ~30,000 tokens (input)
- Model response: ~2,000 tokens (output)
| Model |
Cost per Request |
| GPT-5.3 |
$0.29 |
| Claude Sonnet 4.6 |
$0.12 |
| Gemini 3.1 Pro |
$0.13 |
| DeepSeek V3 |
$0.01 |
Scenario 2: Daily News Analysis (100 articles)
- Input: ~500,000 tokens/day
- Output: ~50,000 tokens/day
| Model |
Cost/Day |
Cost/Month |
| GPT-5.3 |
$5.20 |
$156 |
| Claude Sonnet 4.6 |
$2.25 |
$67.50 |
| Gemini 3.1 Pro |
$2.28 |
$68.25 |
| DeepSeek V3 |
$0.19 |
$5.64 |
Scenario 3: Agentic Trading System (24/7)
- Requests per day: ~1,000
- Average input: 10,000 tokens
- Average output: 1,000 tokens
- Monthly: 300M input + 30M output
| Model |
Cost/Month |
| GPT-5.3 |
$3,120 |
| Claude Opus 4.6 |
$6,750 |
| Claude Sonnet 4.6 |
$1,350 |
| Gemini 3.1 Pro |
$1,365 |
| DeepSeek V3 |
$114 |
Hidden Costs
Price per token is not the only factor:
Rate Limits
- OpenAI: 500-10,000 RPM (depends on tier)
- Anthropic: 1,000-4,000 RPM
- Google: up to 60,000 RPM
- DeepSeek: throttling under heavy load
Latency
- GPT-5.3: ~800ms TTFT
- Claude Sonnet 4.6: ~600ms TTFT
- Gemini 3.1 Pro: ~500ms TTFT
- DeepSeek V3: ~1200ms TTFT (due to server geography)
Reliability (Uptime)
- OpenAI: 99.8% (occasional incidents)
- Anthropic: 99.9%
- Google: 99.95%
- DeepSeek: 99.5% (young infrastructure)
Recommendations
| Use Case |
Best Choice |
Reason |
| Bulk data analysis |
DeepSeek V3 |
Price |
| Mission-critical decisions |
Claude Opus 4.6 |
Quality |
| Coding |
Claude Sonnet 4.6 |
SWE-Bench |
| Long context |
Gemini 3.1 Pro |
1M tokens |
| Budget option |
Qwen 3 7B (self-hosted) |
Free |
Prices continue to fall. What costs $100/month today could cost $20 a year from now. Plan your infrastructure with this trend in mind.
Discussion
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