MODEL PROFILE

Meta-Llama-3.1-8B-Instruct-FP8-dynamic

furiosa-ai · Meta-Llama-3.1-8B-Instruct-FP8-dynamic

This repository contains RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8-dynamic together with a Furiosa Executable Bundle (FXB) for running it on FuriosaAI RNGD with Furiosa-LLM. The same model also runs on other frameworks (such as vLLM, SGLang, and Transformers); for usage with those, see the upstream RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8-dynamic model card. Llama-3.1-8B-Instruct is Meta's 8B instruction-tuned model, an auto-regressive dense transformer optimized for multilingual dialogue, instruction following, and tool usage. This is the FP8-dynamic quantized variant published by RedHatAI, derived from meta-llama/Llama-3.1-8B-Instruct. Its intended use is the same as the upstream RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8-dynamic, and it is released under the Llama 3.1 Community License. The linear (Transformer block) weights are quantized to FP8 (static), and activations use dynamic FP8 quantization at runtime. Activations are quantized per token at inference time rather than with offline calibration.

Text generationlicense:llama3.1
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/30 08:14:45
OVERVIEW

Model overview

This repository contains RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8-dynamic together with a Furiosa Executable Bundle (FXB) for running it on FuriosaAI RNGD with Furiosa-LLM. The same model also runs on other frameworks (such as vLLM, SGLang, and Transformers); for usage with those, see the upstream RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8-dynamic model card. Llama-3.1-8B-Instruct is Meta's 8B instruction-tuned model, an auto-regressive dense transformer optimized for multilingual dialogue, instruction following, and tool usage. This is the FP8-dynamic quantized variant published by RedHatAI, derived from meta-llama/Llama-3.1-8B-Instruct. Its intended use is the same as the upstream RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8-dynamic, and it is released under the Llama 3.1 Community License. The linear (Transformer block) weights are quantized to FP8 (static), and activations use dynamic FP8 quantization at runtime. Activations are quantized per token at inference time rather than with offline calibration.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.

Source / channelInputOutputBilling unitCollected at
No verified prices yet. Check the source channel.

Estimate monthly base token costs

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Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.

INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

Do open weights permit free commercial use?

Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.

Are these real-time billing prices?

These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.

Sources & traceability

许可证:llama3.1。模型介绍与第三方评测均以原来源的具体版本和方法为准。