[GH-ISSUE #9739] gemma3 embeddings support #6366

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opened 2026-04-12 17:52:51 -05:00 by GiteaMirror · 3 comments
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Originally created by @rectalogic on GitHub (Mar 13, 2025).
Original GitHub issue: https://github.com/ollama/ollama/issues/9739

What is the issue?

gemma3:1b fails to generate embeddings, other models work.

$ curl http://localhost:11434/api/embed -d '{
                                    "model": "gemma3:1b",
                                    "input": "Llamas are members of the camelid family"
                                  }'
{"model":"gemma3:1b","embeddings":[null],"total_duration":795587042,"load_duration":644392083,"prompt_eval_count":10}⏎

Relevant log output

time=2025-03-13T13:49:34.664-04:00 level=INFO source=server.go:624 msg="llama runner started in 0.50 seconds"
time=2025-03-13T13:49:34.846-04:00 level=WARN source=runner.go:429 msg="generation of embedding outputs not yet supported"
[GIN] 2025/03/13 - 13:49:34 | 200 |  818.674917ms |       127.0.0.1 | POST     "/api/embed"

OS

macOS

GPU

Apple

CPU

Apple

Ollama version

0.6.0

Originally created by @rectalogic on GitHub (Mar 13, 2025). Original GitHub issue: https://github.com/ollama/ollama/issues/9739 ### What is the issue? gemma3:1b fails to generate embeddings, other models work. ```sh-session $ curl http://localhost:11434/api/embed -d '{ "model": "gemma3:1b", "input": "Llamas are members of the camelid family" }' {"model":"gemma3:1b","embeddings":[null],"total_duration":795587042,"load_duration":644392083,"prompt_eval_count":10}⏎ ``` ### Relevant log output ```shell time=2025-03-13T13:49:34.664-04:00 level=INFO source=server.go:624 msg="llama runner started in 0.50 seconds" time=2025-03-13T13:49:34.846-04:00 level=WARN source=runner.go:429 msg="generation of embedding outputs not yet supported" [GIN] 2025/03/13 - 13:49:34 | 200 | 818.674917ms | 127.0.0.1 | POST "/api/embed" ``` ### OS macOS ### GPU Apple ### CPU Apple ### Ollama version 0.6.0
GiteaMirror added the bug label 2026-04-12 17:52:51 -05:00
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Owner

@dhirajpatra commented on GitHub (Apr 26, 2025):

Yes same here with Docker, MAC i7

private_ai_rag_graph-rag_service-1 | INFO:httpx:HTTP Request: POST http://ollama_server_lite:11434/api/embed "HTTP/1.1 500 Internal Server Error"
private_ai_rag_graph-rag_service-1 | ERROR:root:[blog_retriever] Error: this model does not support embeddings (status code: 500)
private_ai_rag_graph-rag_service-1 | ERROR:root:Chat processing failed.
private_ai_rag_graph-rag_service-1 | Traceback (most recent call last):
private_ai_rag_graph-rag_service-1 | File "/app/app.py", line 40, in chat
private_ai_rag_graph-rag_service-1 | reply = run_rag_chain(query=input_msg.text) # Ensure this is a valid string or dict
private_ai_rag_graph-rag_service-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
private_ai_rag_graph-rag_service-1 | File "/app/graph/rag_graph.py", line 73, in run_rag_chain
private_ai_rag_graph-rag_service-1 | result = rag_graph.invoke(initial_state)
private_ai_rag_graph-rag_service-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
private_ai_rag_graph-rag_service-1 | File "/usr/local/lib/python3.11/site-packages/langgraph/pregel/init.py", line 2795, in invoke
private_ai_rag_graph-rag_service-1 | for chunk in self.stream(
private_ai_rag_graph-rag_service-1 | File "/usr/local/lib/python3.11/site-packages/langgraph/pregel/init.py", line 2433, in stream
private_ai_rag_graph-rag_service-1 | for _ in runner.tick(
private_ai_rag_graph-rag_service-1 | File "/app/graph/rag_graph.py", line 36, in retrieve
private_ai_rag_graph-rag_service-1 | raise ValueError("Retriever tool failed")
private_ai_rag_graph-rag_service-1 | ValueError: Retriever tool failed
private_ai_rag_graph-rag_service-1 | During task with name 'retrieve' and id '4b23d69e-2279-89b9-910c-1bb115861060'
private_ai_rag_graph-rag_service-1 | INFO: 172.19.0.4:42642 - "POST /chat HTTP/1.1" 500 Internal Server Error
private_ai_rag_graph-rag_service-1 | INFO: 127.0.0.1:41316 - "POST /runs/batch HTTP/1.1" 200 OK

<!-- gh-comment-id:2832230138 --> @dhirajpatra commented on GitHub (Apr 26, 2025): Yes same here with Docker, MAC i7 private_ai_rag_graph-rag_service-1 | INFO:httpx:HTTP Request: POST http://ollama_server_lite:11434/api/embed "HTTP/1.1 500 Internal Server Error" private_ai_rag_graph-rag_service-1 | ERROR:root:[blog_retriever] Error: this model does not support embeddings (status code: 500) private_ai_rag_graph-rag_service-1 | ERROR:root:Chat processing failed. private_ai_rag_graph-rag_service-1 | Traceback (most recent call last): private_ai_rag_graph-rag_service-1 | File "/app/app.py", line 40, in chat private_ai_rag_graph-rag_service-1 | reply = run_rag_chain(query=input_msg.text) # Ensure this is a valid string or dict private_ai_rag_graph-rag_service-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private_ai_rag_graph-rag_service-1 | File "/app/graph/rag_graph.py", line 73, in run_rag_chain private_ai_rag_graph-rag_service-1 | result = rag_graph.invoke(initial_state) private_ai_rag_graph-rag_service-1 | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ private_ai_rag_graph-rag_service-1 | File "/usr/local/lib/python3.11/site-packages/langgraph/pregel/__init__.py", line 2795, in invoke private_ai_rag_graph-rag_service-1 | for chunk in self.stream( private_ai_rag_graph-rag_service-1 | File "/usr/local/lib/python3.11/site-packages/langgraph/pregel/__init__.py", line 2433, in stream private_ai_rag_graph-rag_service-1 | for _ in runner.tick( private_ai_rag_graph-rag_service-1 | File "/app/graph/rag_graph.py", line 36, in retrieve private_ai_rag_graph-rag_service-1 | raise ValueError("Retriever tool failed") private_ai_rag_graph-rag_service-1 | ValueError: Retriever tool failed private_ai_rag_graph-rag_service-1 | During task with name 'retrieve' and id '4b23d69e-2279-89b9-910c-1bb115861060' private_ai_rag_graph-rag_service-1 | INFO: 172.19.0.4:42642 - "POST /chat HTTP/1.1" 500 Internal Server Error private_ai_rag_graph-rag_service-1 | INFO: 127.0.0.1:41316 - "POST /runs/batch HTTP/1.1" 200 OK
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@pepitoenpeligro commented on GitHub (May 11, 2025):

It's not problem from Ollama, it's Gemma3

curl http://localhost:11434/api/embed -d '{
  "model": "gemma3:latest",
  "input": "Who is the winner of Eurovision Song Contest 2022?"
}'
{"error":"this model does not support embeddings"}
<!-- gh-comment-id:2870024689 --> @pepitoenpeligro commented on GitHub (May 11, 2025): It's not problem from Ollama, it's Gemma3 ```bash curl http://localhost:11434/api/embed -d '{ "model": "gemma3:latest", "input": "Who is the winner of Eurovision Song Contest 2022?" }' {"error":"this model does not support embeddings"} ```
Author
Owner

@dhirajpatra commented on GitHub (May 12, 2025):

Yes, I have changed the embedding model for ollama. Thanks

<!-- gh-comment-id:2870438225 --> @dhirajpatra commented on GitHub (May 12, 2025): Yes, I have changed the embedding model for ollama. Thanks
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Reference: github-starred/ollama#6366