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Comparison · ai-ml-platforms
LiteLLM vs RAGFlow
A side-by-side editorial comparison of LiteLLM and RAGFlow — release velocity, themes, recent moves, and the top alternatives to consider.
LiteLLM vs RAGFlow: at a glance
What is LiteLLM?
LiteLLM's 1.109 dev build stacks 704 PRs and 15 required config changes.
LiteLLM is patching four stable lines (1.103 to 1.106) in lockstep, most recently with leaner failure logs, a proxy-level GCS logger config and a new cosign signing key. On Oct 28 it opened a 1.109.0 dev line with 704 merged PRs and 15 items flagged as action required. Those include a new image-verification key, Gemini 3.6 Flash rejecting temperature/top_p/top_k, no more local token-count estimates, and budget edits on keys restricted to admins.
What is RAGFlow?
RAGFlow's dev builds settle permission ownership while the rest is migrations and test plumbing.
RAGFlow is shipping several dev builds a day ahead of its v1.0 line. This week's builds fix a migration, update the base DB model, add a model-group hook, start the standalone DeepDoc server before infrastructure, and keep enterprise test placeholders in the open-source tree. An earlier 10-23 build aligned resource and agent ownership with the new permission model.
LiteLLM vs RAGFlow: editorial side-by-side
LiteLLM
5.0AI-ML-PLATFORMS
LiteLLM's 1.109 dev build stacks 704 PRs and 15 required config changes.
◆ Current state
LiteLLM is patching four stable lines (1.103 to 1.106) in lockstep, most recently with leaner failure logs, a proxy-level GCS logger config and a new cosign signing key. On Oct 28 it opened a 1.109.0 dev line with 704 merged PRs and 15 items flagged as action required. Those include a new image-verification key, Gemini 3.6 Flash rejecting temperature/top_p/top_k, no more local token-count estimates, and budget edits on keys restricted to admins.
◆ Where it's heading
The stable lines get hardening and backports, while the next minor is moving the gateway toward stricter defaults: tighter key and budget permissions, explicit max_tokens for unmapped Anthropic models, and provider-side token counting. The size of the action-required list means upgrades are turning into real migrations for self-hosters.
◆ Prediction
Expect more 1.109 dev and rc builds that trim or document the breaking list before a stable 1.109.0, while the 1.103 to 1.106 lines keep getting matching patches.
RAGFlow
7.5AI-ML-PLATFORMS
RAGFlow's dev builds settle permission ownership while the rest is migrations and test plumbing.
◆ Current state
RAGFlow is shipping several dev builds a day ahead of its v1.0 line. This week's builds fix a migration, update the base DB model, add a model-group hook, start the standalone DeepDoc server before infrastructure, and keep enterprise test placeholders in the open-source tree. An earlier 10-23 build aligned resource and agent ownership with the new permission model.
◆ Where it's heading
The permission work that began with the schema migration and tenant roles is wrapping up with ownership rules, while the Go rewrite gets refactors for testability and startup order. The keep-EE-placeholders change shows the open-source and enterprise editions sharing one tree.
◆ Prediction
Expect a v1.0.0 release candidate that packages tenant roles and permissions, with model groups as a likely new configuration surface.
Alternatives to LiteLLM and RAGFlow
Other ai-ml-platforms products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either LiteLLM or RAGFlow.
AnythingLLM
AnythingLLM's Docker image can now run models itself, no Ollama or LM Studio required.
MLflow
MLflow 3.17.2 records dataset, scorer and agent lineage on every GenAI evaluation run.
Kubeflow
Kubeflow's main repo is now a signpost: real releases live in seven subprojects.
Label Studio
Label Studio's only tracked signal is a nightly build toward 1.24.
Mem0
Mem0 is teaching coding agents to search memory less and trust it more.
See all LiteLLM alternatives → · See all RAGFlow alternatives →
Recent activity from LiteLLM and RAGFlow
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1d agoRAGFlowDev build: Chinese UI label fixes
- 1d agoRAGFlowDev build: internal refactor
- 1d agoLiteLLMLiteLLM 1.109 dev: 704 PRs, 15 changes need action
- 1d agoRAGFlowDev build: Docling parser reports page positions and page count
- 1d agoLiteLLMv1.106.5: leaner failure logs, GCS logger uses proxy config
- 1d agoLiteLLMv1.105.6: failure-log and GCS logger fixes backported
- 1d agoLiteLLMv1.104.8: failure-log and GCS logger fixes backported
- 1d agoLiteLLMv1.103.10: failure-log and GCS logger fixes backported
- 2d agoRAGFlowDev build: Aliyun ASR audio now goes via DashScope storage
- 3d agoRAGFlowDev build: testable pprof startup, test split
- 3d agoRAGFlowDev build keeps enterprise test placeholders in OSS
- 4d agoLiteLLMv1.105.5: startup crash fix and scanner-clean images
Frequently asked questions
What is the difference between LiteLLM and RAGFlow?
They serve adjacent needs but don't currently overlap on shipped themes. RAGFlow is currently shipping more aggressively (velocity 7.5 vs 5.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is LiteLLM better than RAGFlow?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. RAGFlow is currently shipping more aggressively (velocity 7.5 vs 5.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other ai-ml-platforms products to evaluate alongside.
What are the best alternatives to LiteLLM?
Top LiteLLM alternatives in ai-ml-platforms are ranked by recent ship velocity. Browse the "LiteLLM alternatives" section above for the current picks, or visit /alternatives/litellm for the full list with editorial commentary on each.
What are the best alternatives to RAGFlow?
Top RAGFlow alternatives in ai-ml-platforms are ranked by recent ship velocity. Browse the "RAGFlow alternatives" section above for the current picks, or visit /alternatives/ragflow for the full list with editorial commentary on each.