MODEL PROOF
Llama 4 Maverick
NOT INDEPENDENTLY RATED
No independent LMArena score is published for this model.
Serving precision differs between offers.
- Independent LMArena score
- Not independently rated
- Context window
- 1.05M
- Maximum output
- 16.38K
- Input modalities
- text, image
- Output modalities
- text
- Published input price
- $0.188 / 1M tokens
- Published output price
- $0.652 / 1M tokens
- Pricing kind
- fixed
Inspect complete billing conditions and endpoint terms below.
Every price dimension · USD per million tokens
| Input | $0.188/M |
|---|---|
| Output | $0.652/M |
| Cached input | Unknown/M |
| Cache write | Unknown/M |
| Cache write 1h | Unknown/M |
| Reasoning | Unknown/M |
Who sells it
The same weights, different shops. Cheapest is not like-for-like when serving precision differs.
Headline cheapest is a lower precision. Like-for-like at the best declared precision is $0.200/M from DeepInfra.
5 provider offers · rates, limits and conditions
Rates are USD per million tokens. Endpoint terms can differ even when the quoted price and precision match. A listed parameter is a provider declaration, not a task-success test.
| Seller | Input | Output | Precision | Uptime (1d) |
|---|---|---|---|---|
| DigitalOceandigitalocean Endpoint terms
| $0.188 | $0.652 | undeclared | 99.87% |
| DeepInfradeepinfra/base Endpoint terms
| $0.200 | $0.800 | fp8 | 99.76% |
| Novitanovita/fp8 Endpoint terms
| $0.270 | $0.850 | fp8 | 99.79% |
| Parasailparasail/fp8 Endpoint terms
| $0.350 | $1.00 | fp8 | 99.95% |
| Googlegoogle-vertex/us-east5 Endpoint terms
| $0.350 | $1.15 | undeclared | — |
Independent scores
No independent benchmark has measured this model. Unrated is not a score of zero.
Capability
| Context window | 1M |
|---|---|
| Max output | 16K |
| Input modes | text, image |
| Tool use | yes |
| Reasoning | no |
| Knowledge cutoff | 2024-08-31 |
| Open weights | yes |
Provenance
| Price source | openrouter.ai |
|---|---|
| Fetched | 2026-09-23 |
| Quality data | unrated |
| Cross-checked | vendor page |
Our take
editorial — not a measurementMaverick is an open-weight candidate for text and image workloads. Review the model’s community licence for the intended deployment rather than treating open weights as unrestricted permission. Hosted sellers can quote different rates and conditions; self-hosting needs its own capacity estimate. Compare task results before assuming that a newer family is a suitable replacement.
Strengths
- Open weights and a community-licence identifier are recorded
- Text and image input are listed
Weaknesses
- Check the output ceiling as well as the context window
- An unlisted cache-read rate does not prove caching is unsupported
Reach for it when
- Self-hosting evaluations within licence terms
- Text and image tasks with explicit output requirements
Avoid it if
- The licence does not cover the intended use
- The required output exceeds the recorded ceiling
Sources: openrouter.ai
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...
Questions this page answers
What does Llama 4 Maverick cost?
$0.188/M in, $0.652/M out in this catalogue, as of the fetch date on this page. That is the API row, not a subscription.
Does Llama 4 Maverick have an independent quality score?
Llama 4 Maverick has no independent quality score in this catalogue. Unrated is not a score of zero.
What beats Llama 4 Maverick?
Llama 4 Maverick has no independent quality score. Unrated is not a score of zero.
Does this page use Artificial Analysis scores for Llama 4 Maverick?
No. Artificial Analysis figures are not published here. Quality on this page is LMArena Elo where a score exists; otherwise the row is unrated.
Does a missing score mean Llama 4 Maverick scored zero?
Unrated is not a score of zero.
Is the cheapest Llama 4 Maverick endpoint the same product?
Headline cheapest is a lower precision. Like-for-like at the best declared precision is $0.200/M from DeepInfra.
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