Got it! I’ll compare the cost of running Llama 3.3, DeepSeek v3, and Phi 3 via APIs (like OpenRouter) versus self-hosting on GPU providers. The analysis will include different token usage breakpoints (10K, 100K, 1M, 10M, 100M tokens/day) and account for multi-GPU setups for high-volume cases.I will identify the cheapest GPU option among AWS, Azure, and GCP, and compare it with two of the most affordable emerging GPU providers. The focus will be strictly on cost, and I'll provide a decision table and/or decision tree to help with choosing between self-hosting and API usage.I'll get back to you once the research is complete!

Cost Comparison: API vs Self-Hosting for Open-Weight LLMs

Token Usage Breakpoints and Cost Estimates

OpenRouter API Costs: OpenRouter offers pay-as-you-go pricing per token for models like Llama 3.3, DeepSeek V3, and Microsoft Phi. These rates are extremely low – on the order of a few cents (or less) per million tokens. For example:

Llama 3.3 (70B) – ~ $0.12 per million prompt tokens and ~$ n0.30 per million generated tokensopenrouter.ai. This works out to roughly $0.21 per 1M tokens (assuming an even split of input/output tokens).
DeepSeek V3 – $0.49 per 1M input tokens and$ n0.89 per 1M output tokensopenrouter.ai ($0.69 per 1M tokens on average).
Microsoft Phi (Phi-3/Phi-4) – $0.07 per 1M input and$ n0.14 per 1M outputopenrouter.ai ($0.10 per 1M combined). At these rates, the daily API cost for various usage levels is negligible until token counts grow very large:
10K tokens/day: API Cost ≈ $0.002 (around a few tenth of a cent per day)openrouter.ai.
100K tokens/day: API Cost ≈ $0.02 (just a few cents per day).
1M tokens/day: API Cost ≈ $0.21 (roughly a couple of dimes per day).
10M tokens/day: API Cost ≈ ** $2.10** per day (about$ n63 per month).
100M tokens/day: API Cost ≈ ** $21** per day (about$ n630 per month). _These estimates use Llama 3.3’s pricing as a representative example. Even DeepSeek V3 (the priciest of the three) would be only ~ $0.69 per 1M tokens[openrouter.ai](https://openrouter.ai/provider/deepinfra#:~:text=%2A%20DeepSeek%3A%20DeepSeek%20V3%20DeepSeek,see%20the%20launch%20announcement) - still under$ n0.70 per day at 1M tokens, and (Llama 3.3 example) | Self-Host on Major Cloud (Azure A100 80GB) | Self-Host on Emerging Provider (Lambda A100 40GB) | | --- | --- | --- | --- | | 10K tokens/day | ~ $0.002 (virtually$ n0)openrouter.ai | ~ $1+ (min. 1 hour GPU billed)[instances.vantage.sh](https://instances.vantage.sh/azure/vm/nc24ads-v4#:~:text=The%20Standard%20NC24ads%20A100%20v4,per%20hour%20with%20spot%20machines) | ~$ n0.4 (min. usage)lambdalabs.com | | 100K tokens/day | ~ $0.02 | ~$ n10 (a few GPU-hours) | ~ $3–$ n4 (a few GPU-hours) | | 1M tokens/day | ~ $0.21[openrouter.ai](https://openrouter.ai/provider/deepinfra#:~:text=,Model%20Card) | ~$ n88– $100 (≈1 full GPU-day) | ~$ n30– $36 (≈1 full GPU-day) | | **10M tokens/day** | ~$ 2.10 | ~ $n880–$ 1,000 (≈10 GPU-days) | ~ $n300–$ 360 (≈10 GPU-days) | | 100M tokens/day | ~ $21.0 | ~$ n8,800– $10,000 (≈100 GPU-days) | ~$ n3,000–$3,600 (≈100 GPU-days) | Notes: The self-hosting costs above assume high-end GPUs and continuous usage to generate the required tokens. In practice, low daily usage (10K–100K tokens) would leave a rented GPU mostly idle (still incurring a minimum charge). High usage (10M–100M) would require multiple GPUs running in parallel to handle the load within a day, hence “GPU-days” scaling roughly with tokens. The API costs remain dramatically lower at every bracket, thanks to OpenRouter’s low per-token pricing.

API vs Self-Hosting – Decision Guide

Considering only the cost (ignoring latency, scaling overhead, engineering effort, etc.), the break-even point for self-hosting versus API is extremely high. Use the following guide to decide:

Low Usage (tens of thousands of tokens/day): Use the API. The cost is effectively zero at this scale, whereas even a minimal GPU instance would cost dollars. For example, 10K tokens costs a fraction of a cent via OpenRouteropenrouter.ai, but you’d pay a few dollars at minimum to run your own GPU for even an hour.
Moderate Usage (up to a few million tokens/day): API is still far more economical. At 1M tokens/day, you’d spend only a few cents to maybe a couple dollars per day on the API, versus tens or hundreds of dollars to keep a GPU runningopenrouter.ai datacrunch.io. Even using cheaper providers, self-hosting would be on the order of $30+ per day for 1M tokens – over 100× the API cost. In this range, API wins on cost by a huge margin.
High Usage (tens of millions of tokens/day): API continues to be more cost-effective in most cases. For example, ~10M tokens/day via API might be only ~$2 daily, whereas renting enough GPUs to serve that volume could run hundreds of dollars daily (even on discount clouds)datacrunch.io www.reddit.com. Unless you have special discounts or already-owned hardware, the API’s pay-per-token model still comes out cheapest.
Very High Usage (approaching ~100M tokens/day or more): This scenario requires a multi-GPU infrastructure, incurring thousands of dollars in daily cloud costs. Even at 100M tokens/day (which is ~3 billion tokens/month), the OpenRouter API would cost on the order of only ~ $600–$ n900/month – vastly cheaper than self-hosting a GPU cluster. Only if you anticipate massive scale beyond these levels (or can secure GPUs at near-zero cost) does self-hosting start to become a consideration purely for cost reasons. In practice, even at 100M/day, API costs (roughly $21/day) are so low that it’s hard to justify the overhead of self-managed GPUs on cost alone. Decision Tree: In summary, for almost any realistic usage volume of these open-weight models, the API-based approach is more economical.
IF your daily token usage is small or moderate (well under tens of millions per day) – choose API (lowest cost).
IF your usage grows to very large scales (tens of millions+ per day) – still choose API in most cases, as the per-token pricing remains dramatically cheaper than running equivalent GPUs.
ONLY IF you reach an extraordinary scale (hundreds of millions of tokens daily or you have access to extremely cheap dedicated GPUs) – consider self-hosting for cost savings. Even then, you’d likely need custom optimizations or bulk GPU deals to beat the API’s cost-efficiencydatacrunch.io www.reddit.com.