Meta, open weights

# Llama 4 Maverick

> Llama 4 Maverick by Meta, released April 2025. Ranked #282 of 354 with a Noometry Index of 30.9. API: $0.19 in / $0.65 out per M tokens. 128K context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/llama-4-maverick
- Last updated: 2026-10-10
- Title: Llama 4 Maverick Benchmarks, Price & Rank (October 2026)

Llama 4 Maverick by Meta ranks 282nd of 354 ranked models on the Noometry Index as of October 2026, with a score of 30.9. Its strongest category is agentic & tool use, where it ranks 91st. API pricing starts at $0.19 per million input tokens and $0.65 per million output tokens, with a 128K-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #282 of 354
- **Index score:** 30.9
- **Evidence:** Confirmed 54 results
- **Provider:** [![](/logos/meta.svg) Meta](https://noometry.com/providers/meta)
- **Released:** April 5, 2025
- **Weights:** Open weights
- **Reasoning:** No
- **Context window:** 128K
- **Max output:** 4K
- **Input price:** $0.19 / M
- **Output price:** $0.65 / M
- **Blended price:** $0.30 / M
- **Output speed:** 456 tokens/s [Kagi](https://help.kagi.com/kagi/ai/llm-benchmark.html)
- **Value:** #58 of 219
- **Knowledge cutoff:** August 2024
- **Input:** text, image
- **Hugging Face:** [meta-llama/Llama-4-Maverick-17B-128E-Instruct](https://huggingface.co/meta-llama/Llama-4-Maverick-17B-128E-Instruct)

## Category scores

Each category score combines every public result we have in that category.

Llama 4 Maverick category scores

1.  Coding 26.6
2.  Agentic & Tool Use 28.2
3.  Reasoning 10.1
4.  Math 26.0
5.  Knowledge 33.4
6.  Multimodal 31.6
7.  Multilingual 42.2
8.  Instruction Following 71.7
9.  Long Context 31.4
10.  Writing & Preference 38.8
11.  020406080

Llama 4 Maverick category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 26.6 | #324 | 7 |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 28.2 | #91 | 1 |
| [Reasoning](https://noometry.com/best/reasoning) | 10.1 | #342 | 10 |
| [Math](https://noometry.com/best/math) | 26.0 | #262 | 4 |
| [Knowledge](https://noometry.com/best/knowledge) | 33.4 | #204 | 7 |
| [Multimodal](https://noometry.com/best/multimodal) | 31.6 | #105 | 2 |
| [Multilingual](https://noometry.com/best/multilingual) | 42.2 | #195 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 71.7 | #146 | 2 |
| [Long Context](https://noometry.com/best/long-context) | 31.4 | #279 | 2 |
| [Writing & Preference](https://noometry.com/best/writing) | 38.8 | #252 | 6 |

## Strengths and weaknesses

Categories where Llama 4 Maverick places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

Llama 4 Maverick: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Instruction Following](https://noometry.com/best/instruction-following) | 71.7 | +0.4 | #146 of 305, top 48% |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 28.2 | −2.2 | #91 of 154, top 60% |
| [Knowledge](https://noometry.com/best/knowledge) | 33.4 | −3.9 | #204 of 314, top 65% |

### Weakest categories

Llama 4 Maverick: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Reasoning](https://noometry.com/best/reasoning) | 10.1 | −13.5 | #342 of 350, top 98% |
| [Coding](https://noometry.com/best/coding) | 26.6 | −12.2 | #324 of 340, top 96% |
| [Long Context](https://noometry.com/best/long-context) | 31.4 | −9.6 | #279 of 296, top 95% |

## Closest competitors

The models ranked just above and below Llama 4 Maverick. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to Llama 4 Maverick
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Mistral Small 3](https://noometry.com/models/mistral-small-3) | #278 | 31.2 | $0.0575 | — | [Compare](https://noometry.com/compare/llama-4-maverick-vs-mistral-small-3) |
| [Phi-4](https://noometry.com/models/phi-4) | #279 | 31.2 | $0.0875 | — | [Compare](https://noometry.com/compare/llama-4-maverick-vs-phi-4) |
| [Mistral Small 3.2](https://noometry.com/models/mistral-small-3-2) | #280 | 31.2 | $0.13 | 68 | [Compare](https://noometry.com/compare/llama-4-maverick-vs-mistral-small-3-2) |
| [Amazon Nova Pro](https://noometry.com/models/amazon-nova-pro) | #281 | 31.0 | $1.40 | — | [Compare](https://noometry.com/compare/amazon-nova-pro-vs-llama-4-maverick) |
| [Phi-4 Mini](https://noometry.com/models/phi-4-mini) | #283 | 30.9 | $0.13 | — | [Compare](https://noometry.com/compare/llama-4-maverick-vs-phi-4-mini) |
| [Gemma 3 27B](https://noometry.com/models/gemma-3-27b) | #284 | 30.8 | $0.10 | 62 | [Compare](https://noometry.com/compare/gemma-3-27b-vs-llama-4-maverick) |
| [Qwen1.5-72B](https://noometry.com/models/qwen1-5-72b) | #285 | 30.8 | — | — | [Compare](https://noometry.com/compare/llama-4-maverick-vs-qwen1-5-72b) |
| [Granite 3.0 2b Instruct](https://noometry.com/models/granite-3-0-2b-instruct) | #286 | 30.8 | — | — | [Compare](https://noometry.com/compare/granite-3-0-2b-instruct-vs-llama-4-maverick) |

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## Benchmark results

Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.

### Coding

Llama 4 Maverick Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [SWE-bench Verified (bash only)](https://noometry.com/benchmarks/swe-bench-bash-only) | 21% | #36 of 39, top 93% |  | [SWE-bench](https://www.swebench.com/) | 2025-07-20 |
| [Aider Polyglot](https://noometry.com/benchmarks/aider-polyglot) | 15.6% | #38 of 44, top 87% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 33.1% | #103 of 121, top 86% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 24.5% | #101 of 119, top 85% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [BigCodeBench Instruct](https://noometry.com/benchmarks/bigcodebench-instruct) | 49.7% | #3 of 64, top 5% |  | [BigCodeBench](https://bigcode-bench.github.io/) | 2025-04-05 |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1302 | #198 of 294, top 68% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [BigCodeBench Complete](https://noometry.com/benchmarks/bigcodebench-complete) | 61.4% | #2 of 66, top 4% |  | [BigCodeBench](https://bigcode-bench.github.io/) | 2025-04-05 |
| [ALE-Bench](https://noometry.com/benchmarks/ale-bench) | 172.97 | #104 of 105, top 100% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Agentic & Tool Use

Llama 4 Maverick Agentic & Tool Use benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Berkeley Function Calling Leaderboard](https://noometry.com/benchmarks/bfcl) | 37.3% | #26 of 49, top 54% | fc | [Berkeley Function Calling Leaderboard](https://gorilla.cs.berkeley.edu/leaderboard.html) |  |

### Reasoning

Llama 4 Maverick Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 0% | #80 of 83, top 97% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SimpleBench](https://noometry.com/benchmarks/simplebench) | 27.7% | #61 of 77, top 80% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Kagi LLM Benchmark](https://noometry.com/benchmarks/kagi-reasoning) | 55.9% | #49 of 99, top 50% |  | [Kagi LLM Benchmark](https://help.kagi.com/kagi/ai/llm-benchmark.html) |  |
| [NYT Connections (extended)](https://noometry.com/benchmarks/nyt-connections) | 8% | #89 of 91, top 98% |  | [Lech Mazur benchmarks](https://github.com/lechmazur/nyt-connections) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 4.4% | #80 of 83, top 97% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 0% | #118 of 134, top 89% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 0% | #118 of 134, top 89% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [EnigmaEval](https://noometry.com/benchmarks/enigmaeval) | 0.6% | #37 of 38, top 98% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1281 | #200 of 297, top 68% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 61.9% | #110 of 151, top 73% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 15.9% | #103 of 125, top 83% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 132.2 | #133 of 213, top 63% |  | [Epoch AI](https://epoch.ai/eci) | 2025-04-06 |
| [ForecastBench](https://noometry.com/benchmarks/forecastbench) | 57.5 | #56 of 72, top 78% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Math

Llama 4 Maverick Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 20.6% | #126 of 173, top 73% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2025-04-08 |
| [Omni-MATH](https://noometry.com/benchmarks/omni-math) | 42.2% | #24 of 57, top 43% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1299 | #185 of 285, top 65% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [MATH Level 5](https://noometry.com/benchmarks/math-level-5) | 73% | #29 of 79, top 37% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2025-04-08 |
| [FrontierMath (Feb 2025 set)](https://noometry.com/benchmarks/frontiermath-2025-02) | 0.7% | #62 of 68, top 92% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2025-04-08 |

### Knowledge

Llama 4 Maverick Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 67% | #102 of 186, top 55% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2025-04-08 |
| [Humanity's Last Exam](https://noometry.com/benchmarks/hle) | 5.7% | #33 of 41, top 81% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [MMLU-Pro](https://noometry.com/benchmarks/mmlu-pro) | 81% | #15 of 58, top 26% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [Confabulations](https://noometry.com/benchmarks/confabulations) (lower is better) | 22.6% | #38 of 51, top 75% |  | [Lech Mazur benchmarks](https://github.com/lechmazur/confabulations) |  |
| [Vectara Hallucination Rate](https://noometry.com/benchmarks/vectara-hallucination) (lower is better) | 8.2% | #37 of 96, top 39% |  | [Vectara Hallucination Leaderboard](https://github.com/vectara/hallucination-leaderboard) |  |
| [GPQA (HELM)](https://noometry.com/benchmarks/helm-gpqa) | 65% | #19 of 57, top 34% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1259 | #190 of 273, top 70% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multimodal

Llama 4 Maverick Multimodal benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Vision](https://noometry.com/benchmarks/arena-vision) | 1142 | #99 of 122, top 82% |  | [LMArena](https://lmarena.ai/leaderboard/vision) | 2026-10-09 |
| [GeoBench](https://noometry.com/benchmarks/geobench) | 52% | #20 of 25, top 80% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SpatialViz-Bench](https://noometry.com/benchmarks/spatialviz-bench) | 31.8% | #8 of 8, top 100% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Multilingual

Llama 4 Maverick Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1269 | #195 of 297, top 66% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1277 | #194 of 285, top 69% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1259 | #181 of 223, top 82% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1291 | #152 of 231, top 66% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1207 | #155 of 211, top 74% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1203 | #159 of 213, top 75% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1286 | #184 of 283, top 66% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1293 | #162 of 226, top 72% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

Llama 4 Maverick Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [IFEval](https://noometry.com/benchmarks/ifeval) | 90.8% | #8 of 57, top 15% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1267 | #198 of 298, top 67% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

Llama 4 Maverick Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Fiction.LiveBench](https://noometry.com/benchmarks/fiction-livebench) | 46.2% | #38 of 47, top 81% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1280 | #203 of 291, top 70% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

Llama 4 Maverick Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1287 | #201 of 297, top 68% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1267 | #194 of 295, top 66% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Short-Story Creative Writing](https://noometry.com/benchmarks/lech-mazur-writing) | 62% | #37 of 39, top 95% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [EQ-Bench Creative Writing](https://noometry.com/benchmarks/eqbench-creative-writing) | 860 | #102 of 115, top 89% |  | [EQ-Bench](https://eqbench.com/creative_writing.html) |  |
| [WildBench](https://noometry.com/benchmarks/wildbench) | 80% | #31 of 57, top 55% |  | [HELM Capabilities](https://crfm.stanford.edu/helm/capabilities/latest/) |  |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1289 | #196 of 295, top 67% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

Llama 4 Maverick API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [azure](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models) | $0.25 | $1 | — | 2026-10-10 |
| [bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html) | $0.24 | $0.97 | — | 2026-10-10 |
| [deepinfra](https://deepinfra.com/models) | $0.20 | $0.80 | — | 2026-10-10 |
| [openrouter](https://openrouter.ai/meta-llama/llama-4-maverick) | $0.19 | $0.65 | $0.05 | 2026-10-10 |
| [vertex](https://cloud.google.com/vertex-ai/generative-ai/docs/models) | $0.35 | $1.15 | — | 2026-10-10 |

[All Meta API prices →](https://noometry.com/llm-pricing/meta) [Estimate your cost →](https://noometry.com/tools/cost-calculator)

## Compare Llama 4 Maverick

-   [Llama 4 Maverick vs Amazon Nova Pro](https://noometry.com/compare/amazon-nova-pro-vs-llama-4-maverick)
-   [Llama 4 Maverick vs Phi-4 Mini](https://noometry.com/compare/llama-4-maverick-vs-phi-4-mini)
-   [Llama 4 Maverick vs Mistral Small 3.2](https://noometry.com/compare/llama-4-maverick-vs-mistral-small-3-2)
-   [Llama 4 Maverick vs Gemma 3 27B](https://noometry.com/compare/gemma-3-27b-vs-llama-4-maverick)
-   [Llama 4 Maverick vs Phi-4](https://noometry.com/compare/llama-4-maverick-vs-phi-4)
-   [Llama 4 Maverick vs Qwen1.5-72B](https://noometry.com/compare/llama-4-maverick-vs-qwen1-5-72b)
-   [Llama 4 Maverick vs GPT-6 Astra](https://noometry.com/compare/gpt-6-astra-vs-llama-4-maverick)
-   [Llama 4 Maverick vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-llama-4-maverick)
-   [Llama 4 Maverick vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-llama-4-maverick)
-   [Llama 4 Maverick vs Kimi K3](https://noometry.com/compare/kimi-k3-vs-llama-4-maverick)
-   [Llama 4 Maverick vs Grok 4.6](https://noometry.com/compare/grok-4-6-vs-llama-4-maverick)
-   [Llama 4 Maverick vs Qwen3.8 Max](https://noometry.com/compare/llama-4-maverick-vs-qwen3-8-max)
-   [Llama 4 Maverick vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-llama-4-maverick)
-   [Llama 4 Maverick vs DeepSeek V4 Pro](https://noometry.com/compare/deepseek-v4-pro-vs-llama-4-maverick)

## Other Meta models

-   [Muse Spark 1.3](https://noometry.com/models/muse-spark-1-3)54.8
-   [Muse Spark](https://noometry.com/models/muse-spark)50.6
-   [Muse Spark 1.2](https://noometry.com/models/muse-spark-1-2)50.3
-   [Muse Spark 1.1](https://noometry.com/models/muse-spark-1-1)49.9
-   [Muse Glimmer](https://noometry.com/models/muse-glimmer)41.7
-   [Codellama 70b Instruct](https://noometry.com/models/codellama-70b-instruct)33.7
-   [Codellama 34b Instruct](https://noometry.com/models/codellama-34b-instruct)30.8
-   [Llama 3.1-405B](https://noometry.com/models/llama-3-1-405b)30.7

## Frequently asked questions

### How good is Llama 4 Maverick?

Llama 4 Maverick by Meta ranks 282nd of 354 ranked models on the Noometry Index as of October 2026, with a score of 30.9. Its strongest category is agentic & tool use, where it ranks 91st. API pricing starts at $0.19 per million input tokens and $0.65 per million output tokens, with a 128K-token context window.

### How much does Llama 4 Maverick cost?

Llama 4 Maverick costs $0.19 per million input tokens and $0.65 per million output tokens on openrouter, with cached input at $0.05.

### What is Llama 4 Maverick's context window?

Llama 4 Maverick accepts up to 128K tokens of input and can write up to 4K tokens in one response.

### Is Llama 4 Maverick open source?

Yes. Llama 4 Maverick's weights are downloadable from Hugging Face (meta-llama/Llama-4-Maverick-17B-128E-Instruct); check the license for commercial terms.

### How fast is Llama 4 Maverick?

Llama 4 Maverick generated about 456 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.

### What are Llama 4 Maverick's strengths and weaknesses?

Relative to other ranked models, Llama 4 Maverick places best in instruction following, agentic & tool use, knowledge and lowest in reasoning, coding, long context.

### What is Llama 4 Maverick best at?

Its best category is agentic & tool use, where it ranks 91st on Noometry.

### Cite this page

Noometry. (2026). Llama 4 Maverick benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/llama-4-maverick

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/llama-4-maverick.md).