Hermes 3 Llama 3.1 405b
hermes-3-llama-3-1-405bhermes-3-llama-3.1-405b- 🆕 Full-parameter finetune of Meta's Llama 3.1 405B foundation model.
- 🏢 Built by Nous Research, hosted here with web search.
- 📏 128K-token context window for long, coherent conversations.
- 🔧 Reliable function calling and structured JSON output support.
- 🎯 User-steerable alignment, giving control to the end user.
- ⚡ Served in FP8 quantization, fitting roughly 430GB VRAM.
- 💬 Strong roleplaying, multi-turn dialogue, and agentic behavior.
- 📚 Licensed under Meta's Llama 3 community license.
Meta Platforms is an American multinational technology company headquartered in Menlo Park, California. Best known for operating Facebook, Instagram, WhatsApp, and Threads, Meta has become one of the most influential players in open-weight AI research through its Llama family of…
Explore 6 more models by Meta Platforms →Hermes 3 Llama 3.1 405B is a frontier-scale, full-parameter finetune of Meta's Llama 3.1 405B foundation model, developed by Nous Research rather than Meta itself. Nous describes it as the first full-parameter fine-tune of the 405B base, with a design philosophy centered on aligning the model to the individual user and granting powerful steering capabilities and control to the end user. It is a generalist model offering a 128K-token context window, reliable function calling, and structured JSON output suitable for software integration.
Relative to its same-family predecessor, Hermes 2, Nous reports that Hermes 3 adds advanced agentic capabilities, improved roleplaying, stronger reasoning, better multi-turn conversation, and improved long-context coherence across the board. These are vendor-stated generational improvements rather than independently verified benchmark figures.
Because the full 405B model requires over 800GB of VRAM in FP16, this build uses NeuralMagic's FP8 quantization to reduce the footprint to roughly 430GB while remaining compatible with the VLLM inference engine. The model is released under Meta's Llama 3 community license, reflecting its Llama base.
Within this catalog, Hermes 3 is the largest and newest text model in its family, sitting alongside Meta's own smaller releases such as Llama 3.3 70B and Llama 3.2 3B. Here it is additionally equipped with web-search capability for retrieval-augmented responses.
This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.
Daily usage · Hermes 3 Llama 3.1 405b · Organic sellers
Top sellers · Hermes 3 Llama 3.1 405b · Organic
- Venice.ai Proxy99.0%
- ▲ Apex Ant0.7%
- Fire Ant 🔥🐜0.2%
- RedPill0.0%
- OpenCheap0.0%
| Seller | Health | Rep↓ | Sales | Tokens | Routing | Input $/M | Cached $/M | Output $/M | Save |
|---|---|---|---|---|---|---|---|---|---|
| Apex TEE Test 0xe672…7955 | — | 0.00 | — | — | gated | $0.495 | $0.495 | $1.35 | −55% |
| antseed-neon-puma-944e 0x6650…944e | — | 0.00 | — | — | gated | $0.3751 | $0.3751not advertised | $1.023 | −66% |
| Meridian AI 0x8c8c…06f5 | — | 0.00 | — | — | gated | $0.1069 | $0.1069not advertised | $0.2916 | −90% |
| Leftermute 0x388b…5389 | — | 0.00 | — | — | gated | $0.10 | $0.10not advertised | $0.2727 | −91% |
| ▲ Apex Ant 0x73b4…e736 | failingmodel gone · 19 h · stale | 81.71 | $0.00 | 9.40k | #1 | $1.20 | $1.20 | $1.20 | — |
"Best price" and the seller table are live Antseed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = buyer trust score (0-100, the Antseed SDK's own formula). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on Antseed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.