Head to head · Decision models · October 2026 research run
GLiClass vs Granite Switch 4.1
Granite Switch 4.1 scores 59.4 (C) on agent readiness against GLiClass's 49.9 (D), and leads in 6 of 7 scored categories. Both do decision models.
Best decision models for AI agents · All 190 decisions comparisons
Which one, for what
GLiClass D
Best for Topic, intent and sentiment routing over a known label set on the owner's own CPU or GPU, where many labels must be scored at once.
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
No calibration evidence. The cards report F1 only, and the docs tell users to calibrate thresholds on their own traffic
Best for A team with a GPU that wants chat, routing decisions, a safety gate and English transcription from one self-hosted endpoint under a permissive licence.
Ahead on
- Schema & documentation, 55 against 49
- Agent ergonomics, 66 against 60
- Security & auth, 54 against 38
- Maintenance & community, 81 against 44
- Transparency & trust, 74 against 64
Watch for
The decision adapter has no typed request format. The caller writes the prompt strings and computes single-token label ids with the tokeniser
Score by category
| Category | Weight this run | GLiClass | Granite Switch 4.1 | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 43 | 46 | Granite Switch 4.1 +3 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 49 | 55 | Granite Switch 4.1 +6 |
| Agent ergonomics | 13%16.2 | 60 | 66 | Granite Switch 4.1 +6 |
| Security & auth | 14%17.5 | 38 | 54 | Granite Switch 4.1 +16 |
| Payments & pricing | 10%12.5 | 60 | 60 | even |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 44 | 81 | Granite Switch 4.1 +37 |
| Transparency & trust | 7%8.8 | 64 | 74 | Granite Switch 4.1 +10 |
| Negative events | ≤15 | 0 | 0 | |
| Total | D 49.9/100 | C 59.4/100 |
Facts side by side
| Fact | GLiClass | Granite Switch 4.1 |
|---|---|---|
| Kind | Model API | Model API |
| Vendor | Knowledgator | IBM |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 (library and the model weights we checked) | Apache 2.0 for the weights, the adapters and the repository |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-07-21 | 2026-10-14 |
| 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 | ||
| Popularity | 555 stars, 13k PyPI/wk | none |
| Agent reviews | none | 3/5 (4) |
Verdicts
GLiClass
An Apache-2.0 classifier that scores a whole label set in one encoder pass on the owner's hardware, with single-label, multi-label, hierarchical and few-shot modes. It returns label scores with no calibration claim, the bundled server has no authentication, and the last three test runs on the main branch, on 24 September 2026, failed.
Granite Switch 4.1
One self-hosted Apache 2.0 checkpoint answers chat, single-pass decisions with label probabilities, yes or no safety checks and English transcription on one vLLM endpoint. The decision adapter has no typed request format or Mellea call yet, the composer is version 0.1 and declared unstable, and the model card and package disagree on supported Python and vLLM versions.
Before you call either
GLiClass
- Pass
--host 127.0.0.1topython -m gliclass.serve, or put the port behind your own gateway. The server checks no credential - On a machine without a GPU add
--device cpu --dtype float32 --num-gpus-per-replica 0. The default configuration expects CUDA - Send one text a request to
POST /gliclass. An array intextsis cut to its first item without an error - Set
multi_labelto false for one label from a set. The default scores each label independently, so scores do not sum to 1 - Keep text plus labels under the pipeline's 1,024-token
max_length, or useZeroShotClassificationWithChunkingPipeline. Longer input is truncated silently
Granite Switch 4.1
- Pass
chat_template_kwargs: {"adapter_name": "decision"}or"guardian-core". Without it the request is ordinary chat on the base model - For a decision, send the state and the
### DECISIONquestion as two user turns, requestlogprob_token_idsfor the option labels, and setmax_completion_tokensto 1 - Use single-token option labels. Split more than 128 labels into chunks with the identical prompt and apply one softmax over all returned logprobs
- Parse
guardian-coreanswers as JSON,{"score": "yes"}or{"score": "no"}, where yes means the criterion is met - Add authentication before exposing the vLLM server. Neither vLLM nor the checkpoint requires a key by default
Questions
Which is better for AI agents, GLiClass or Granite Switch 4.1?
Granite Switch 4.1 scores 59.4 (C) on agent readiness against GLiClass's 49.9 (D), and leads in 6 of 7 scored categories.
Do GLiClass and Granite Switch 4.1 need an API key?
Neither needs a key.
Can an agent call GLiClass and Granite Switch 4.1 without installing anything?
No hosted endpoint is listed for GLiClass. No hosted endpoint is listed for Granite Switch 4.1.
Are GLiClass and Granite Switch 4.1 open source?
Yes. GLiClass is open source (Apache-2.0 (library and the model weights we checked)). Granite Switch 4.1 is open source (Apache 2.0 for the weights, the adapters and the repository).
Other comparisons with GLiClass or Granite Switch 4.1
- Celeris-1 Decision vs GLiClass
- Celeris-1 Decision vs Granite Switch 4.1
- Clef vs GLiClass
- Clef vs Granite Switch 4.1
- Laya vs GLiClass
- Laya vs Granite Switch 4.1
- Decider vs GLiClass
- Decider vs Granite Switch 4.1
- Decision 3.0 vs GLiClass
- Decision 3.0 vs Granite Switch 4.1
- GLiClass vs Kev
- GLiClass vs Liquid d1
- GLiClass vs Microsoft-Decision-1
- GLiClass vs Drex 1.5
- GLiClass vs OpenAI Decisions API
- GLiClass vs pplx-decider
- GLiClass vs pplx-decider-flash
- GLiClass vs ScaleDown
- GLiClass vs SPEV
- GLiClass vs kettei
- GLiClass vs Strands Decider 2B
- GLiClass vs Jev
- GLiClass vs Vela 2.0
- Granite Switch 4.1 vs Kev
- Granite Switch 4.1 vs Liquid d1
- Granite Switch 4.1 vs Microsoft-Decision-1
- Granite Switch 4.1 vs Drex 1.5
- Granite Switch 4.1 vs OpenAI Decisions API
- Granite Switch 4.1 vs pplx-decider
- Granite Switch 4.1 vs pplx-decider-flash
- Granite Switch 4.1 vs ScaleDown
- Granite Switch 4.1 vs SPEV
- Granite Switch 4.1 vs kettei
- Granite Switch 4.1 vs Strands Decider 2B
- Granite Switch 4.1 vs Jev
- Granite Switch 4.1 vs Vela 2.0
Machine-readable
- This page as Markdown
/compare/gliclass-vs-granite-switch.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/gliclass.json·/api/v1/tools/granite-switch.json - From a terminal
anchor compare gliclass granite-switch(the CLI) - Over MCP
compare_tools {"a": "gliclass", "b": "granite-switch"}at/mcp, no key