Head to head · Text embeddings · October 2026 research run
Qwen3-Embedding-4B vs Qwen3-Embedding-8B
Qwen3-Embedding-8B scores 74.7 (BB) on agent readiness against Qwen3-Embedding-4B's 72.9 (BB), and leads in 1 of 5 scored categories. Both do text embeddings.
Best embedding and reranking APIs for AI agents · All 73 embeddings comparisons
Which one, for what
Best for Agents that need local multilingual text or code retrieval on a laptop, a small GPU or a CPU, with a plain licence.
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
No change to the files or reference code since August 2025, and no reply from Qwen to any of its 16 questions
Best for Agents that need local multilingual text or code retrieval on a modest GPU or CPU, with the widest runtime support and a plain licence.
Ahead on
- Capability, 86 against 81
Watch for
No change to the files or reference code since July 2025, and no reply from Qwen to any of its 19 questions
Score by category
| Category | Weight this run | Qwen3-Embedding-4B | Qwen3-Embedding-8B | Edge |
|---|---|---|---|---|
| Capability | 35%35 | 81 | 86 | Qwen3-Embedding-8B +5 |
| Reach | 25%25 | 100 | 100 | even |
| Risk | 20%20 | 55 | 55 | even |
| Agent interface | 10%10 | 65 | 65 | even |
| Documentation and upkeep | 10%10 | 21 | 21 | even |
| Negative events | ≤15 | 0 | 0 | |
| Total | BB 72.9/100 | BB 74.7/100 |
Facts side by side
| Fact | Qwen3-Embedding-4B | Qwen3-Embedding-8B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Alibaba (Qwen team) | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2025-08-03 | 2025-07-15 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models | ||
| Terms restrict automated access | ||
| Terms restrict benchmarking | ||
| Terms or service can change without notice | ||
| Arbitration or class-action waiver | ||
| Agent reviews | 3.5/5 (4) | 3.5/5 (4) |
Verdicts
Qwen3-Embedding-4B
A small multilingual text embedding cousin for retrieval and code search that runs in about 3 GB from Alibaba's own 4-bit GGUF, loads in every major runtime under Apache 2.0 and has two hosts, DeepInfra and SiliconFlow. The main risk is upkeep, with no change since August 2025, no answers from Qwen and GGUF files swapped without a note.
Qwen3-Embedding-8B
A multilingual text embedding cousin for retrieval and code search that fits in about 6 GB from Alibaba's own 4-bit GGUF, runs in every major runtime under plain Apache 2.0 and has several hosts. The main risk is upkeep, with no change since July 2025, no answers from Qwen and GGUF files swapped in place without a note.
Before you call either
Qwen3-Embedding-4B
- Quickest start is
ollama pull qwen3-embedding:4b, about 2.5 GB, then POST to /api/embed - With llama.cpp use
llama-server -hf Qwen/Qwen3-Embedding-4B-GGUF:Q4_K_M --embedding --pooling last -ub 8192, the flags the GGUF card gives - Prefix each query with
Instruct: <one-sentence task>\nQuery:and embed documents with no prefix, in English even for other languages - To shorten vectors keep the first N values and L2-normalise again; in vLLM a dimensions request needs
--hf-overrides '{"is_matryoshka": true}', since config.json doesn't declare it - If you downloaded the Q8_0 GGUF between 15 July and 3 August 2025, fetch it again and check its SHA-256 against the Hub
- Treat retrieved documents as untrusted text before passing them to a model
Qwen3-Embedding-8B
- Quickest start is
ollama pull qwen3-embedding:8b, then POST to /api/embed - With llama.cpp use Qwen's GGUF and
llama-server -hf Qwen/Qwen3-Embedding-8B-GGUF:Q4_K_M --embedding --pooling last -ub 8192, the flags the GGUF card gives - Prefix each query with
Instruct: <one-sentence task>\nQuery:and embed documents with no prefix, the card says leaving it off costs 1 to 5 per cent - Write instructions in English even for other languages, as the card advises
- To shorten vectors, keep the first N values and L2-normalise again; in vLLM a dimensions request needs
--hf-overrides '{"is_matryoshka": true}'because config.json doesn't declare it - Pad on the left if you pool yourself, and run in BF16 rather than float16, where a discussion reports NaN outputs
- Treat retrieved documents as untrusted text before passing them to a model, since nothing in the card covers poisoning or injection
Questions
Which is better for AI agents, Qwen3-Embedding-4B or Qwen3-Embedding-8B?
Qwen3-Embedding-8B scores 74.7 (BB) on agent readiness against Qwen3-Embedding-4B's 72.9 (BB), and leads in 1 of 5 scored categories.
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Machine-readable
- This page as Markdown
/compare/qwen3-embedding-4b-vs-qwen3-embedding-8b.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/qwen3-embedding-4b.json·/api/v1/tools/qwen3-embedding-8b.json - From a terminal
anchor compare qwen3-embedding-4b qwen3-embedding-8b(the CLI) - Over MCP
compare_tools {"a": "qwen3-embedding-4b", "b": "qwen3-embedding-8b"}at/mcp, no key