Head to head · Open-weight models you run yourself · October 2026 research run
LFM3-Audio-2B vs ZAYA1-8B
LFM3-Audio-2B and ZAYA1-8B score within a point of each other on agent readiness, 61 (C) and 61 (C). ZAYA1-8B leads on risk. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 6359 open weights comparisons
Which one, for what
Best for Voice agents on a laptop or phone that need speech in, speech out and tool calls from one small model
Ahead on
- Agent interface, 85 against 60
Watch for
Only llama.cpp and Ollama run it in a release, though the card lists vLLM and SGLang
ZAYA1-8B C
Best for People who want a small, fast reasoning model for maths and code and can live without tool calling
Ahead on
- Risk, 55 against 40
Watch for
Tool calling needs a parser that only Zyphra's vLLM fork has
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Agent interface LFM3-Audio-2B +25
LFM3-Audio-2B 85
Chat template 20, chat_template.jinja in the repository (9,328 characters), with roles, audio, tools, deferred tools and tool results. Tool-calling format 25, the card and Liquid's tool-use page document tools passed through tools= in apply_chat_template, calls returned as XML and results sent back as tool messages. Trained tool calling 20, the template loops over every entry in an assistant turn's tool_calls, so several calls fit in one turn, and the card names turning spoken requests into tool calls as one of its four uses. Structured output 5, the card says the model is designed for structured outputs without saying how to ask for JSON. Liquid's API guide documents response_format with lfm3-1.7b as its example. Reasoning control 10, the card documents reasoning per request for text replies: the caller prefills the assistant turn with an open think tag to let the model reason, or a closed one for a direct answer, with a use_thinking example. Context 5, 32K tokens of input and output per the card. 20 + 25 + 20 + 5 + 10 + 5 = 85.
ZAYA1-8B 60
Chat template 20, chat_template.jinja in the repository (10,700 characters). Tool-calling format 10, only the template and a fork say it. Trained tool calling 10, the template takes tools and renders calls, and the card recommends settings for agent use, but it doesn't say the model was trained for tool calling or for several calls in a turn, so the lower band. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, the template has an enable_thinking switch, and the card names the qwen3 reasoning parser, which returns the reasoning apart from the answer. Context 10, 131,072 positions in config.json, for an architecture Zyphra trained end to end, so the config is the model's own. 20 + 10 + 10 + 0 + 10 + 10 = 60.
Risk ZAYA1-8B +15
LFM3-Audio-2B 40
File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, files in the LiquidAI organisation, which Liquid's docs page for the model and its blog post link to (10). Safety evaluation 0, no safety results on the card or in Liquid's blog post for the LFM3 family, neither of which mentions safety testing. Agent guidance 0, Nothing on prompt injection, an instruction hierarchy, what refusals cover or safeguards to add. Licence risk 10, 15 less 5 for the $10M annual revenue threshold on commercial use. Security programme 0, no way to report a flaw found. 15 + 15 + 0 + 0 + 10 + 0 = 40.
ZAYA1-8B 55
File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the Zyphra organisation, which the card ties to zyphra.com's blog post for the model (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 0, no way to report a flaw on the card, and www.zyphra.com has no security.txt. 25 + 15 + 0 + 0 + 15 + 0 = 55.
Score by category
| Category | Weight this run | LFM3-Audio-2B | ZAYA1-8B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 80 | 80 | even |
| Risk | 20%20 | 40 | 55 | ZAYA1-8B +15 |
| Agent interface | 10%10 | 85 | 60 | LFM3-Audio-2B +25 |
| Documentation and upkeep | 10%10 | 52 | 50 | LFM3-Audio-2B +2 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 61/100 | C 61/100 |
Facts side by side
| Fact | LFM3-Audio-2B | ZAYA1-8B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Liquid AI | Zyphra |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-11-03 | 2026-07-02 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
Verdicts
LFM3-Audio-2B
A 2B model that listens and speaks on an 8 GB machine, transcribes and translates 19 languages and turns spoken requests into tool calls. Only llama.cpp and Ollama run it in a release. The context is 32K, voice chat is English only, Liquid hasn't answered the repository's questions, and there are no safety results or data sources.
ZAYA1-8B
A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety.
Before you call either
LFM3-Audio-2B
- Start it with
llama-server -hf LiquidAI/LFM3-Audio-2B-GGUF:Q4_K_M --jinjaorollama run lfm3-audio - llama.cpp ships examples/realtime_client.py for live speech with this model
- Prefill the assistant turn with an open think tag to let it reason before a text reply
- The context is 32K
- Voice chat is English only, while transcription, synthesis and translation cover 19 languages and locales
- Liquid doesn't recommend it for agentic coding or complex multi-step reasoning
ZAYA1-8B
- Use it for reasoning, maths and code. Don't count on tool calling outside Zyphra's vLLM fork
- Run it with Transformers 5.22.2 or SGLang 0.5.23, which have the model built in
- Use temperature 1.0 and top_p 0.95 in general, and temperature 0.6 for agent and code work
- Download
Zyphra/ZAYA1-8B, not the legacy repository, for the released runtimes - The quantised repositories have no licence tag. The main one is Apache 2.0
Questions
Which is better for AI agents, LFM3-Audio-2B or ZAYA1-8B?
LFM3-Audio-2B and ZAYA1-8B score within a point of each other on agent readiness, 61 (C) and 61 (C). ZAYA1-8B leads on risk.
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Machine-readable
- This page as Markdown
/compare/lfm3-audio-2b-vs-zaya1-8b.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/lfm3-audio-2b.json·/api/v1/tools/zaya1-8b.json - From a terminal
anchor compare lfm3-audio-2b zaya1-8b(the CLI) - Over MCP
compare_tools {"a": "lfm3-audio-2b", "b": "zaya1-8b"}at/mcp, no key