Clarifai Ranks on the Prime for Efficiency and Value-Effectivity

Synthetic Evaluation, an impartial benchmarking platform, evaluated suppliers serving GPT-OSS-120B throughout latency, throughput, and worth. In these assessments, Clarifai’s Compute Orchestration delivered 0.27 s Time to First Token (TTFT) and 313 tokens per second at a blended worth close to $0.16 per 1M tokens. These outcomes place Clarifai within the benchmark’s “most engaging” zone for prime velocity and low worth.

Contained in the Benchmarks: How Clarifai Stacks Up

Synthetic Evaluation benchmarks give attention to three core metrics that map on to manufacturing workloads:

• Time to First Token (TTFT): the delay from request to the primary streamed token. Decrease TTFT improves responsiveness in chatbots, copilots, and agent loops.

• Tokens per second (throughput): the common streaming fee, a robust indicator of completion velocity and effectivity.

• Blended worth per million tokens: a normalized price metric that accounts for each enter and output tokens, permitting apples-to-apples comparisons throughout suppliers.

On GPT-OSS-120B, Clarifai achieved:

• TTFT: 0.27 s 

• Throughput: 313 tokens/sec

• Blended worth: $0.16 per 1M tokens

• Total: Ranked within the benchmark’s “most engaging” quadrant for velocity and price effectivity

These numbers validate Clarifai’s potential to stability low latency, excessive throughput, and price optimization—key components for scaling massive fashions like GPT-OSS-120B.

Under is a comparability of output velocity versus worth throughout main suppliers for GPT-OSS-120B. Clarifai stands out within the “most engaging quadrant,” combining excessive throughput with aggressive pricing.

Output Pace vs. Worth

Under chart compares latency (time to first token) towards output velocity. Clarifai demonstrates one of many lowest latencies whereas sustaining top-tier throughput—putting it among the many best-in-class suppliers.

Latency vs. Output Pace

GPU and {Hardware}-Agnostic Inference at Scale with Clarifai

Clarifai’s Compute Orchestration is designed to maximise efficiency and effectivity whatever the underlying {hardware}.

Key components embrace:

• Vendor-agnostic deployment: Seamlessly deploy fashions on any CPU, GPU, or accelerator in our SaaS, your individual cloud or on-premises infrastructure, or in air-gapped environments with out lock-in.

• Autoscaling and right-sizing: Dynamic scaling ensures assets adapt to workload spikes whereas minimizing idle prices.

• GPU fractioning and effectivity: Methods that maximize utilization by operating a number of fashions or tenants on the identical GPU fleet.

• Runtime flexibility: Help for frameworks equivalent to TensorRT-LLM, vLLM, and SGLang throughout GPU generations like H100 and B200, giving groups the flexibleness to optimize for both latency or throughput.

This orchestration-first method issues for GPT-OSS-120B, a compute-intensive Combination-of-Specialists mannequin, the place cautious tuning of schedulers, batching methods, and runtime decisions can drastically have an effect on efficiency and price.

What these outcomes imply for engineering groups

For builders and platform groups, Clarifai’s benchmark efficiency interprets into clear advantages when deploying GPT-OSS-120B in manufacturing:

1. Sooner, smoother person experiences
   With a median TTFT of ~0.27 s, purposes ship prompt suggestions. In multi-step agent workflows, decrease TTFT compounds to considerably cut back response instances.

2. Improved price effectivity
   Excessive throughput (~313 tokens/sec) mixed with ~$0.16 per 1M tokens permits groups to serve extra requests per GPU hour whereas maintaining budgets predictable.

3. Operational flexibility
   Groups can select between latency-optimized or throughput-optimized runtimes and scale seamlessly throughout infrastructures, avoiding vendor lock-in.

4. Relevant to various use circumstances

   • Enterprise copilots: quicker draft technology and real-time help

   • RAG and analytics pipelines: environment friendly summarization of lengthy paperwork with decrease prices

   • Agentic workflows: repeated instrument calls with minimal latency overhead

Check out GPT-OSS-120B

Benchmarks are helpful, however one of the best ways to judge efficiency is to attempt the mannequin your self. Clarifai makes it easy to experiment and combine GPT-OSS-120B into actual workflows.

1. Take a look at within the Playground

You’ll be able to immediately discover GPT-OSS-120B in Clarifai’s Playground with an interactive UI—excellent for speedy experimentation, immediate design, and side-by-side mannequin comparisons.

Strive GPT-OSS-120B within the Playground

2. Entry by way of the API

For manufacturing use, GPT-OSS-120B is totally accessible by Clarifai’s OpenAI-compatible API. This implies you may combine the mannequin with the identical tooling and workflows you already use for OpenAI fashions—whereas benefiting from Clarifai’s orchestration effectivity and cost-performance benefits.

Broad SDK and runtime assist

Builders can name GPT-OSS-120B throughout a variety of environments, together with:

• Python (Clarifai Python SDK, OpenAI-compatible API, gRPC)

• Node.js (Clarifai SDK, OpenAI-compatible purchasers, Vercel AI SDK)

• JavaScript, PHP, Java, cURL and extra

This flexibility lets you combine GPT-OSS-120B immediately into your present pipelines with minimal code adjustments.

Python instance (OpenAI-compatible API)

See the Clarifai Inference documentation for particulars on authentication, supported SDKs, and superior options like streaming, batching, and deployment flexibility.

Conclusion

Synthetic Evaluation’s impartial analysis of GPT-OSS-120B highlights Clarifai as one of many main platforms for velocity and price effectivity. By combining quick token streaming (313 tok/s), low latency (0.27 s TTFT), and a aggressive blended worth ($0.16/M tokens), Clarifai delivers the type of efficiency that issues most for production-scale inference.

For ML and engineering groups, this implies extra responsive person experiences, environment friendly infrastructure utilization, and confidence in scaling GPT-OSS-120B with out unpredictable prices. Learn the complete Synthetic Evaluation benchmarks.

Should you’d like to debate these outcomes or have questions on operating GPT-OSS-120B in manufacturing, be part of us in our Discord Channel. Our workforce and group are there to assist with deployment methods, GPU decisions, and optimizing your AI infrastructure.