- Type
- Open weightsApache License 2.0
- Params
- 14.8B
- Context
- 131K
about 98K words of context
Our take
Written Aug 3, 2026Qwen3 is a compact downloadable text model from Alibaba with a permissive Apache licence and a 131,072-token request limit. It is positioned for budget API inference and open-weights deployment where licensing freedom matters more than measured quality scores.
Pick this when you need a permissive licence for commercial use or redistribution, or for long-context text tasks up to 131,072 tokens without multimodal needs. Choose it if low API cost is the priority over verified quality data. Skip it if you need benchmark-backed quality assurance, multimodal input, or guaranteed consistent throughput across endpoints.
The case for it
- Apache License 2.0 allows unrestricted commercial use, fine-tuning and redistribution.
- Lowest tracked API price in its family, with output rates well under half those at some hosts.
- 131,072-token request limit, a large figure for its parameter class.
The case against it
- No measured quality benchmarks in our data — no Elo, MMLU, coding or reasoning scores available.
- Output rates vary by more than half across endpoints from the same provider.
- Some hosts charge several times more for output than the cheapest tracked option.
How good is it?
We hold no score for this model.
We look for every model we track on every board we watch, and none of them has turned up Qwen3 14B — so there is no intelligence, coding, agentic or writing score to show you, not a low one, none.
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. 11.7 GB spare means a 10% error in the size would not change the answer.
GeForce RTX 5090 · 32 GB
Room to spare. 19.7 GB spare means a 10% error in the size would not change the answer.
Apple M1 (8-core GPU) · 16 GB
Borderline fit on an estimated size. It leaves 0.9 GB spare on a size we calculated rather than measured, and a 10% error either way would 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 6 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
- $0.23 in / $0.91 out
- Context served
- 131K
- Throughput
- Not measured
| Provider | In / out per 1M tokens | Context | Throughput | Trains on prompts | Logs prompts | Zero retention |
|---|---|---|---|---|---|---|
| NextBitint4 | $0.10 / $0.22 | 41K | 45 tok/s | No | No | Confirmed |
| DeepInfrafp8 | $0.12 / $0.24 | 41K | not measured | Unknown | Unknown | Unknown |
| DeepInfrafp8 | $0.12 / $0.24 | 41K | 67 tok/s | No | No | Confirmed |
| OpenRouter | $0.23 / $0.91 | 131K | not measured | Unknown | Unknown | Unknown |
| Alibaba Cloud | $0.23 / $0.91 | 131K | 57 tok/s | No | Yesunknown period | Unknown |
| Alibaba Cloudfp8 | $0.23 / $0.91 | 131K | 45 tok/s | No | Yesunknown period | Unknown |
DeepInfraAcross the 6 listings we hold: 4 say they do not train on prompts, 0 say they do and 2 do not say. 2 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 |
|---|---|---|---|
| NextBitint4 | ✗ | ✓ | ✓ |
| DeepInfrafp8 | |||
| DeepInfrafp8 | ✓ | ✓ | ✓ |
| OpenRouter | ✓ | ✓ | ✓ |
| Alibaba Cloud | ✓ | ✓ | ✗ |
| Alibaba Cloudfp8 | ✓ | ✓ | ✗ |
Tool calling: 4 of 6 listings say yes, 1 says no, 1 publishes no parameter list. JSON output: 5 of 6 listings say yes, 1 publishes no parameter list. Strict schema: 3 of 6 listings say yes, 2 say no, 1 publishes no parameter list.
Models people weigh against Qwen3 14B
When we formed this view
Dates behind this page
Prices last checked 5d 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.
- No board we watch has turned up a score, so we hold no quality figures at all.
- 1 of 6 listings publish no parameter list, so what their API accepts is unknown to us.
- Nothing we hold says whether an endpoint streams, so we do not show it either way.
- 2 of 6 listings do not say whether they train on prompts.
- We hold no cached-input rate for any of its listings.
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
- Qwen/Qwen3-14B
- Architecture
- Dense
- Modality record
- text->text
- Catalogue slug
- qwen-qwen3-14b