Granite 4.1 8B
IBM · released Apr 6, 2026 · ibm-granite/granite-4.1-8b
- Type
- Open weightsApache License 2.0
- Params
- 8.8B
- Context
- 131K
about 98K words of context
Our take
Written Aug 2, 2026Granite 4.1 is an 8.8-billion-parameter text model from IBM with a permissive Apache licence. Its measured coding score is its strongest suit, though its overall chat standing is modest and it handles text only.
Pick this for low-cost coding tasks where the Arena Coding score is the signal that matters, or for Apache-licensed deployment needing a 131,072-token request limit at very low hosted cost. Use it on CoreWeave if you need a provider that discloses throughput. Skip it if you need image, video or audio handling, if web development coding is your main work, or if you want frontier-level overall chat quality.
The case for it
- Strongest measured skill is coding, with a 46.1-point gap above its own overall chat score.
- Apache License 2.0 allows commercial use, fine-tuning and redistribution.
- 131,072-token request limit is large for its parameter class.
- Very low hosted inference cost on both available providers.
The case against it
- Overall chat quality lags well behind frontier models, with no higher overall score measured.
- Web development coding specifically trails its own general coding score by 159.2 points.
- Text-to-text only: no image, video or audio handling, and only one provider discloses throughput.
How good is it?
IntelligencePuzzles, maths, exam questions
Arena Text (overall)122nd of 143 · 1306.6
CodingWriting and fixing code on its own
Arena Coding118th of 143 · 1353.9
AgenticPlanning, calling tools, staying on task
Nobody we watch has scored Granite 4.1 8B for this. We would take the rating from Arena Agent (IPS).
WritingWe do not rate this
Two boards come close and neither tests writing: Arena Creative Writing asks people which of two replies they prefer, and LiveBench Language tests whether a model understood a passage. So we show where Granite 4.1 8B placed and give it no mark out of five.
These tests check whether a model follows instructions — a precondition for all the work above, but not a measure of how well that work is done, which is why they get no rating.
Every published score for this model7 scoresEvery figure we hold, from 7 boards, with who ran it and a link to the source — including the boards no rating above is built on.
Can you run it yourself?
- Fits in memory
- weights load entirely on the card
- Spills to system RAM
- some weights offload; much slower
- Too large
- will not load even with offload
- est
- size is calculated; the verdict could change by 10%
Comfortable fit
GeForce RTX 4090 · 24 GB
Room to spare. 15.5 GB spare means a 10% error in the size would not change the answer.
GeForce RTX 5090 · 32 GB
Room to spare. 23.5 GB spare means a 10% error in the size would not change the answer.
Apple M1 (8-core GPU) · 16 GB
Room to spare. 4.7 GB spare means a 10% error in the size would not change the answer.
Memory use by level
Against a 24 GB card.
All 3 sizes here are calculated, not measured. We hold no measured file for this model, so each size comes from the parameter count and every verdict above inherits that uncertainty.
Check against your own machine → · All 71 devices, with every size →
Or rent it from someone else
Cheapest of 2 live listings. Picked at the widest standard context we hold, within one quantisation slice, so the numbers beside it are a price one host actually charges.
- per 1M tokens
- $0.050 in / $0.10 out
- Context served
- 131K
- Throughput
- Not measured
| Provider | In / out per 1M tokens | Context | Throughput | Trains on prompts | Logs prompts | Zero retention |
|---|---|---|---|---|---|---|
| OpenRouter | $0.050 / $0.10 | 131K | not measured | Unknown | Unknown | Unknown |
| CoreWeavebf16 | $0.050 / $0.10 | 131K | 134 tok/s | No | No | Confirmed |
Across the 2 listings we hold: 1 say they do not train on prompts, 0 say they do and 1 do not say. 1 appear in the zero-retention registry we check; the rest are unknown to us rather than confirmed either way.
What each host's API supports
From the parameter list each endpoint publishes. Streaming is omitted: nothing we hold reports it, for any model.
- ✓
- Supported
- ✗
- Not supported
- Not published
- host gave no parameter list
| Provider | Tool calling | JSON output | Strict schema |
|---|---|---|---|
| OpenRouter | ✓ | ✓ | ✓ |
| CoreWeavebf16 | ✓ | ✓ | ✓ |
Tool calling: 2 of 2 listings say yes. JSON output: 2 of 2 listings say yes. Strict schema: 2 of 2 listings say yes.
When we formed this view
Dates behind this page
Prices last checked 6h ago
What we do not know about this model yet
- We hold no measured file for it, so all 3 sizes on this page are calculated from the parameter count.
- Nothing we hold says whether an endpoint streams, so we do not show it either way.
- 1 of 2 listings do not say whether they train on prompts.
Licence and identifiers
What the licence allowsApache License 2.0, what it allows commercially, and the identifiers you need to pull this model — its Hugging Face repo, our slug and a machine-readable card.
Licence
Apache License 2.0
Fully permissive: commercial use, redistribution, and derivatives allowed. Requires attribution and a copy of the license. Includes an express patent grant.
Identifiers
- Hugging Face
- ibm-granite/granite-4.1-8b
- Architecture
- Dense
- Modality record
- text->text
- Catalogue slug
- ibm-granite-granite-4-1-8b