Grok Models

24 modelsGeneral models from $0.2/M inputUp to 1M context

Usage

Last 2 days · 2026-09-10 to 2026-09-11

Tokens

0

Requests

4

Models in use

3 of 24

Tokens per day, stacked by model

01109-102026-09-10 — 0 tokens2026-09-11 — 0 tokens

Which models that traffic went to

    Share of 0 tokens. 3 models with traffic report no token counts and cannot be ranked here, including grok-4-1-fast-non-reasoning and grok-4-1-fast-reasoning — they are in the request view.

    The two views disagree on purpose: a model can take a large share of the calls and a small share of the tokens — many short requests — or the reverse. Which one matters depends on whether your cost is driven by call volume or by prompt length. Measured on AIHubMix over the last 2 days, counting the 24 model IDs listed on this page; traffic routed through upstream-specific IDs that are not in the public catalog is not included.

    All 24 Grok Models

    Open in model list
    Grok models on AIHubMix with input and output modalities, context length, maximum output, price per million tokens including cache read and cache write rates, and measured throughput and latency.
    Modalities
    grok-4-1-fast-non-reasoningTakes text, vision, returns text.1M2M$0.2$0.5/M$0.05/M
    grok-4-1-fast-reasoningTakes text, vision, returns text.1M2M$0.2$0.5/M$0.05/M
    grok-4-fast-non-reasoningTakes text, vision. Output modality not published.1M$0.2$0.5/M$0.05/M137 tok/s2.70 s
    grok-4-fast-reasoningTakes text, vision. Output modality not published.1M$0.2$0.5/M$0.05/M137 tok/s2.70 s
    grok-4.3Takes text, vision. Output modality not published.1M$1.25$2.5/M$0.2/M
    grok-4.5Takes text, vision. Output modality not published.500K$2$6/M$0.5/M
    grok-code-fast-1Takes text, vision. Output modality not published.256K$0.2$1.5/M$0.02/M87 tok/s1.26 s
    grok-build-0.1Takes text, vision, returns text.256K2M$1$2/M$0.2/M36 tok/s0.80 s
    grok-4Takes text, vision. Output modality not published.256K$3.3$16.5/M$0.825/M54 tok/s2.70 s
    grok-3-mini$0.3$0.501/M
    grok-3-mini-beta$0.33$0.5511/M
    grok-3-mini-fast-beta$0.33$2.2001/M
    grok-4.20-0309-non-reasoning$1.25$2.5/M$0.2/M
    grok-2-1212$1.8$9/M
    grok-2-vision-1212Takes text, vision, returns text.$1.8$9/M
    grok-4.20-beta-0309-non-reasoning$2$6/M$0.2/M
    grok-4.20-beta-0309-reasoning$2$6/M$0.2/M
    grok-4.20-multi-agent-beta-0309$2$6/M$0.2/M
    grok-3$3$15/M
    grok-3-beta$3$15/M
    grok-3-fast$5.5$27.5/M
    grok-3-fast-beta$5.5$27.5/M
    grok-vision-betaTakes text, vision, returns text.$5.6$16.8/M
    grok-4-pro$60$300/M$15/M54 tok/s2.70 s

    Prices are USD per million tokens; cache read and cache write are the rates for prompt-cache hits and for writing a prompt into the cache. Throughput and latency are measured on AIHubMix — the same figures the model detail page shows — not vendor claims. A dash means the catalog does not publish that field for that model, which is not the same as the model not supporting it.

    Grok on AIHubMix

    Which Grok model should I start with?

    grok-4-1-fast-non-reasoning at $0.2/M input — the cheapest entry here that declares tool calling, and it carries a 1M context. Move up to grok-4-pro when answer quality matters more than cost, or to grok-4-1-fast-reasoning for long-form reasoning.

    Which of these models reason before answering?

    3 of the 24 models here declare a reasoning phase — they work through the problem before producing an answer, which helps on multi-step problems at the cost of extra output tokens. Use the Reasoning filter above the table to see them. The catalog does not record anything further about how they differ, so this page does not sort them into families.

    Why are there several entries for the same model?

    Because each row is a route you can call, not a model release. Some IDs name an upstream (azure-, alicloud-, cc-), and some differ only in capitalisation, kept so older integrations keep working.

    The catalog does not carry a field saying which of those a given row is, so this page does not sort them into buckets it would have to invent. Every row shows that route’s own price, context and speed — compare those directly, and open a model to see the upstreams that serve it.

    How is cached input billed?

    The Cache read column is the rate for input tokens served from the prompt cache — for example grok-4.20-beta-0309-non-reasoning bills cache hits at 10% of the input rate and grok-4.20-beta-0309-reasoning bills cache hits at 10% of the input rate. Cache write is the surcharge for putting a prompt into the cache in the first place, and only a few upstreams bill it separately. A dash in either column means the catalog carries no cache rate for that model, so plan on paying the full input rate.

    Do I need a separate Grok account?

    No. One AIHubMix key covers every model on this page, and switching between them is a change to the model string — billing, rate limits, and logs stay in one place.

    Start calling Grok in one line

    One key, one endpoint, 750 models across 29 model authors.