[KongchangAI]
ModelLlama 3.1 8B

Llama 3.1 8B Instruct

An 8-billion-parameter instruction-tuned large language model released by Meta as part of the Llama 3.1 series, supporting multilingual use and long context.

Timeline (last 90 days)

Nov 4

On the AlpacaEval 2.0 benchmark (with GPT-4o as the judge), after three rounds of DNO-Prct iteration, the length-controlled (LC) win rate of Llama 3.1 8B Instruct against GPT-4o rose from 31.7% to 45.3%.

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Nov 4

The tuned Llama 3.1 8B Instruct surpasses Llama 3.1 70B Instruct on all reported win-rate metrics.

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Nov 4

The research team independently reimplemented the DNO-Prct pipeline rather than directly using the original authors' code, and validated it on Llama 3.1 8B Instruct and Mistral 7B Instruct v0.1.

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Oct 14

During writing, a local WebSocket test loop was actually run; the bridge completed the config handshake, spoke the first sentence, and streamed back a coherent 18 chunks from llama-3.1-8b-instruct, and ping and interruption handling both worked as documented.

Expired50%
Oct 14

Connecting an open-source model to the Retell Custom LLM slot requires only a bridge service of about 90 lines.

Unverified50%
Oct 14

When using llama-3.1-8b-instruct bridged to EcoHash, calculated at about 2000 input tokens and 250 output tokens per minute for a typical customer service call at a unit price of $0.10/1M, the token cost is about $0.0003/minute.

Expired50%
Oct 14

The bridge is located in the integrations/retell directory of ecohash-examples, uses the llama-3.1-8b-instruct model by default, and is priced at $0.10 / 1M tokens for both input and output.

Unverified50%
Oct 14

The measured performance of llama-3.1-8b-instruct on EcoHash is a TTFT of 205 ms (p95) and about 143 tokens/second for a single stream.

Expired50%

All Facts (5)

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