# Qwen3-Embedding-4B vs Qwen3-Embedding-8B

> Qwen3-Embedding-8B scores 74.7 (BB) to Qwen3-Embedding-4B's 72.9 (BB) for text embeddings. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/qwen3-embedding-4b-vs-qwen3-embedding-8b
- Markdown: https://www.anchorterminal.com/compare/qwen3-embedding-4b-vs-qwen3-embedding-8b.md (~2,150 tokens)
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- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-10-21

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.

- Qwen3-Embedding-4B: grade BB, 72.9/100, rank #3 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-embedding-4b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-embedding-4b.json
- Qwen3-Embedding-8B: grade BB, 74.7/100, rank #1 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-embedding-8b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-embedding-8b.json
- Best embedding and reranking APIs for AI agents: https://www.anchorterminal.com/best/embeddings/index.md
- All 73 embeddings comparisons: https://www.anchorterminal.com/compare/embeddings/index.md

## Which one, for what

### Qwen3-Embedding-4B (BB)

Good for: Agents that need local multilingual text or code retrieval on a laptop, a small GPU or a CPU, with a plain licence.

Watch for: No change to the files or reference code since August 2025, and no reply from Qwen to any of its 16 questions

### Qwen3-Embedding-8B (BB)

Good 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 | Qwen3-Embedding-4B | Qwen3-Embedding-8B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 81 | 86 | Qwen3-Embedding-8B +5 |
| Reach | 25% (25 this run) | 100 | 100 | even |
| Risk | 20% (20 this run) | 55 | 55 | even |
| Agent interface | 10% (10 this run) | 65 | 65 | even |
| Documentation and upkeep | 10% (10 this run) | 21 | 21 | even |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **72.9 · BB** | **74.7 · BB** | |

## 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

1. Quickest start is `ollama pull qwen3-embedding:4b`, about 2.5 GB, then POST to /api/embed
2. 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
3. Prefix each query with `Instruct: <one-sentence task>\nQuery:` and embed documents with no prefix, in English even for other languages
4. 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
5. 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
6. Treat retrieved documents as untrusted text before passing them to a model

### Qwen3-Embedding-8B

1. Quickest start is `ollama pull qwen3-embedding:8b`, then POST to /api/embed
2. 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
3. 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
4. Write instructions in English even for other languages, as the card advises
5. 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
6. Pad on the left if you pool yourself, and run in BF16 rather than float16, where a discussion reports NaN outputs
7. 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.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/qwen3-embedding-4b-vs-qwen3-embedding-8b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/qwen3-embedding-4b-vs-qwen3-embedding-8b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "qwen3-embedding-4b", "b": "qwen3-embedding-8b"}`. From a terminal: `anchor compare qwen3-embedding-4b qwen3-embedding-8b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/qwen3-embedding-4b.json and https://www.anchorterminal.com/api/v1/tools/qwen3-embedding-8b.json

## Other comparisons with Qwen3-Embedding-4B or Qwen3-Embedding-8B

- [EmbeddingGemma 300M vs Qwen3-Embedding-4B](https://www.anchorterminal.com/compare/embeddinggemma-300m-vs-qwen3-embedding-4b.md)
- [EmbeddingGemma 300M vs Qwen3-Embedding-8B](https://www.anchorterminal.com/compare/embeddinggemma-300m-vs-qwen3-embedding-8b.md)
- [Granite Embedding Small English R2 vs Qwen3-Embedding-4B](https://www.anchorterminal.com/compare/granite-embedding-small-english-r2-vs-qwen3-embedding-4b.md)
- [Granite Embedding Small English R2 vs Qwen3-Embedding-8B](https://www.anchorterminal.com/compare/granite-embedding-small-english-r2-vs-qwen3-embedding-8b.md)
- [jina-embeddings-v5-omni-small vs Qwen3-Embedding-4B](https://www.anchorterminal.com/compare/jina-embeddings-v5-omni-small-vs-qwen3-embedding-4b.md)
- [jina-embeddings-v5-omni-small vs Qwen3-Embedding-8B](https://www.anchorterminal.com/compare/jina-embeddings-v5-omni-small-vs-qwen3-embedding-8b.md)
- [Qwen3-Embedding-0.6B vs Qwen3-Embedding-4B](https://www.anchorterminal.com/compare/qwen3-embedding-0-6b-vs-qwen3-embedding-4b.md)
- [Qwen3-Embedding-0.6B vs Qwen3-Embedding-8B](https://www.anchorterminal.com/compare/qwen3-embedding-0-6b-vs-qwen3-embedding-8b.md)
- [Qwen3-Embedding-4B vs Qwen3-VL-Embedding-2B](https://www.anchorterminal.com/compare/qwen3-embedding-4b-vs-qwen3-vl-embedding-2b.md)
- [Qwen3-Embedding-4B vs Qwen3-VL-Embedding-8B](https://www.anchorterminal.com/compare/qwen3-embedding-4b-vs-qwen3-vl-embedding-8b.md)
- [Qwen3-Embedding-8B vs Qwen3-VL-Embedding-2B](https://www.anchorterminal.com/compare/qwen3-embedding-8b-vs-qwen3-vl-embedding-2b.md)
- [Qwen3-Embedding-8B vs Qwen3-VL-Embedding-8B](https://www.anchorterminal.com/compare/qwen3-embedding-8b-vs-qwen3-vl-embedding-8b.md)

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