Throughput (tokens / sec)
median 131.3tokens/s
Serverless LLM Inference API
LLM Inference Engineered for Better Margins
Run open-source models through an OpenAI-compatible API at up to 80% lower cost — on high-throughput GPUs in our own EU data center.
- $10 free credits
- OpenAI-compatible
- EU-owned and operated
- No training on your data
Built in the EU, for production traffic
EU-owned, not just EU-hosted
Your requests run on GPUs we own, in our own EU data center, run by a European company.
Predictable throughput
The throughput you measure on day one is the throughput you plan production around.
Production controls included
Automatic failover, spending limits, and EU-only data handling keep high-volume inference controlled and safe to scale.
Designed for lower prices. Engineered for performance.
Optimized inference runtime
GPU routing tuned for throughput and latency — the same speed and reliability, at consistently lower cost.
Speculative decoding
Faster token generation and sub-second responses, with identical output.
Efficient GPU utilization
Infrastructure built for sustained inference load, not occasional demo traffic.
Discounted cached input
Reused context bills at a lower cache-read rate, so repeated workloads cost less.
Up to 80% Lower Cost
Same models.
Same tokens.
Lower bill.
Compare Entrim’s pricing, powered by an optimized inference runtime, against other providers using the same token counts per request.
Estimate your Savings
Select a model
▾
Token usage(Usage split, 10:1: 9B input - 909M output)
10B
| Provider | Input / 1M | Output / 1M | Monthly est. |
|---|---|---|---|
| AkashML | $0.45 | $3.20 | $7,000.00 |
| io.net | $0.44 | $3.15 | $6,863.64 |
| Chutes | $0.40 | $3.00 | $6,363.64 |
| Entrim | $0.10 | $0.40 | $1,272.73 Save up to 80% |
Try it for free
$10 credits included
Models ready for your workload. Instant. Stable. Scalable.
DeepSeek V4.1 Flash
New
Beta
Agentic coding with image input and 1M context
1M
FP8
Vision
Thinking
Tool Calling
- Input / M
- $0.20
- Output / M
- $0.60
- Cached / M
- $0.005
GLM 5.3 Flash
Turbo
Multimodal coding agents with 1M context
1M
NVFP4
Vision
Video
Thinking
- Input / M
- $0.10
- Output / M
- $0.35
- Cached / M
- $0.0175
Dense multimodal coding with thinking control
262K
FP8
Vision
Video
Thinking
- Input / M
- $0.10
- Output / M
- $0.40
- Cached / M
- $0.04
Performance verified by production load
Time to first token (TTFT)
median 1,247ms
Performance data measured on Entrim.ai EU infrastructure under production load over the last 7 days (daily medians, UTC dates).
99.9%
Uptime
Measured across the last 30 days.
99.8%
Request success rate
Successful API responses across the last 30 days.
200B+
Tokens/day
Built to handle sustained high-volume inference workloads.
Switch infrastructure without switching code
Keep your SDK. Keep your prompts. Change three lines — base URL, API key, model name. Then compare quality, latency, and cost on your own workload with $10 free credit.
Code examples
curl -X POST "https://api.entrim.ai/v1/chat/completions" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $ENTRIM_API_KEY" \ -d '{ "model": "your-model-name", "messages": [ { "role": "user", "content": "Why do they call it a building if it is already built?" } ] }'SDKs & docs
Use familiar SDK patterns with quickstart examples for common production setups.
OpenAI-compatible
Keep the request format your team already knows.
No cold starts
Production requests are served without model spin-up delays.
Know where your inference data goes
No retention.
No training
Prompts and outputs are processed for inference, not stored after completion, and never used to train models.
ZDR Available
No training
Output discarded
EU-only
data handling
Prompts, outputs, and request metadata stay on EU soil — no transfer to third countries, no sub-processors outside the EU. DPA available.
EU-owned and operated
GDPR compliant
DPA available
Security controls
for API traffic
Requests are encrypted, access is isolated by API key, and traffic is handled with tenant-level separation.
Encrypted requests
API key isolation
Tenant separation
Compliance
posture
Controls are being built around recognised security frameworks, with limited operational metadata used for billing, monitoring, latency, and abuse prevention.
SOC 2 aligned / IN PROGRESS
ISO 27001 aligned / IN PROGRESS
Built for products where inference cost matters
Entrim fits teams running repeated, measurable LLM workloads — where every request, document, conversation, or user action has a cost.
AI-native products
For companies where LLM inference is part of the product COGS — AI assistants, vertical SaaS, copilots, companion apps, and generative workflows running at user scale.
SaaS teams adding AI features
For product teams shipping AI into existing apps — summaries, search, recommendations, automation, and user-facing AI actions that need predictable cost per feature.
Voice and customer agents
For conversational AI, support automation, and agent workflows where latency, retry loops, and per-interaction economics directly affect margins.
Document and knowledge workflows
For RAG, document extraction, contract review, claims processing, internal knowledge assistants, and other high-volume text-heavy pipelines.
1,500+ developers already run on Entrim
I’ve already tested multiple inference providers, including Makora, Baseten, Novita, and Crof. So far, this one seems to deliver the fastest response times and the best overall performance for my use case.
JanMinecraft plugin developer
After testing multiple open-weight LLM inference providers, Entrim stood out from the crowd. Most platforms suffer from slow speeds due to being oversubscribed or lack trustworthy jurisdictions and data retention policies. Entrim ticked all the boxes. Because they are an EU-based company that completely self-hosts their own infrastructure rather than acting as a middleman, I finally have total peace of mind regarding data privacy. On top of that, the service is incredibly fast and easy to use.
DavidHead of Delivery
We’ve integrated Entrim into AgentOS as a custom provider, and it has been working very well. We’ve been using it as our primary provider for around a month, and overall the experience has been very positive.
KazımFounder of AgentOS
You’ve made good progress on quality. I’ve been using your DeepSeek model and gave Qwen 3.8 27B a brief try. I can see that your quantization is solid and that you’re actively working on quality.
Mykyta TkachenkoCEO at KDB Soft
Overall, I’m very happy with the service — I think your product is coming at exactly the right time, and both the performance and speed have been great so far. No complaints on latency or reliability.
Jiri
I have been using Entrim’s DeepSeek model with DeepSeek’s harness and it works so good, I am really impressed!
AsadApp developer
FAQ
Here are the most common questions users ask before getting started.
Test Entrim with your real workload
Run your real workload through Entrim with $10 free credits. Compare output speed, latency, and cost against what you pay now.