Grok 4.20 Beta 0309 (Reasoning) Intelligence, Performance & Price Analysis
Model summary
Intelligence
Artificial Analysis Intelligence Index
Speed
Output tokens per second
Input Price
USD per 1M tokens
Output Price
USD per 1M tokens
Verbosity
Output tokens from Intelligence Index
Metrics are compared against models of the same class:
- Non-reasoning models → compared only with other non-reasoning models
- Reasoning models → compared across both reasoning and non-reasoning
- Open weights models → compared only with other open weights models of the same size class:
- Tiny: ≤4B parameters
- Small: 4B–40B parameters
- Medium: 40B–150B parameters
- Large: >150B parameters
- Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:
- <$0.15 per 1M tokens
- $0.15–$1 per 1M tokens
- >$1 per 1M tokens
| Reasoning | Yes This page shows the reasoning version of this model. A non-reasoning variant may also exist. |
|---|---|
| Input modality | Supports: text, image |
| Output modality | Supports: text |
| Context window | 2m ~3000 A4 pages of size 12 Arial font |
Grok 4.20 Beta 0309 (Reasoning) is amongst the leading models in intelligence and reasonably priced when comparing to other models of similar price. It's also notably fast, however somewhat verbose. The model supports text and image input, outputs text, and has a 2m tokens context window.
Grok 4.20 Beta 0309 (Reasoning) scores 48 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (averaging 28). When evaluating the Intelligence Index, it generated 54M tokens, which is somewhat verbose in comparison to the average of 13M.
Pricing for Grok 4.20 Beta 0309 (Reasoning) is $2.00 per 1M input tokens (somewhat expensive, average: $1.60) and $6.00 per 1M output tokens (moderately priced, average: $10.00). In total, it cost $484.42 to evaluate Grok 4.20 Beta 0309 (Reasoning) on the Intelligence Index.
At 265 tokens per second, Grok 4.20 Beta 0309 (Reasoning) is notably fast (61).
Intelligence
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if the weights are available but commercial use is limited (typically requires obtaining a paid license).
Intelligence Evaluations
While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.
Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Openness
Artificial Analysis Openness Index: Results
Intelligence Index Comparisons
Intelligence vs. Price
While higher intelligence models are typically more expensive, they do not all follow the same price-quality curve.
Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Intelligence Index Token Use & Cost
Output Tokens Used to Run Artificial Analysis Intelligence Index
The number of tokens required to run all evaluations in the Artificial Analysis Intelligence Index (excluding repeats).
Cost to Run Artificial Analysis Intelligence Index
The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input and output token pricing and the number of tokens used across evaluations (excluding repeats).
Context Window
Context Window
Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.
Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).
Pricing
Pricing: Input and Output Prices
Price per token included in the request/message sent to the API, represented as USD per million Tokens.
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Intelligence vs. Price (Log Scale)
While higher intelligence models are typically more expensive, they do not all follow the same price-quality curve.
Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Pricing Comparison of Grok 4.20 Beta 0309 (Reasoning) API Providers
Speed
Measured by Output Speed (tokens per second)
Output Speed
Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Output Speed vs. Price
Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).
Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).
Latency
Measured by Time (seconds) to First Token
Latency: Time To First Answer Token
Time to first answer token received, in seconds, after API request sent. For reasoning models, this includes the 'thinking' time of the model before providing an answer. For models which do not support streaming, this represents time to receive the completion.
End-to-End Response Time
Seconds to output 500 Tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed
End-to-End Response Time
Seconds to receive a 500 token response. Key components:
- Input time: Time to receive the first response token
- Thinking time (only for reasoning models): Time reasoning models spend outputting tokens to reason prior to providing an answer. Amount of tokens based on the average reasoning tokens across a diverse set of 60 prompts (methodology details).
- Answer time: Time to generate 500 output tokens, based on output speed
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Model Size (Open Weights Models Only)
Model Size: Total and Active Parameters
The total number of trainable weights and biases in the model, expressed in billions. These parameters are learned during training and determine the model's ability to process and generate responses.
The number of parameters actually executed during each inference forward pass, expressed in billions. For Mixture of Experts (MoE) models, a routing mechanism selects a subset of experts per token, resulting in fewer active than total parameters. Dense models use all parameters, so active equals total.
Comparisons to Grok 4.20 Beta 0309
- Grok 4.20 Beta 0309
gpt-oss-120B (high)- GPT-5.4 Pro (xhigh)
- gpt-oss-20B (high)
- GPT-5.4 (xhigh)
- GPT-5.2 (xhigh)
- GPT-5.3 Codex (xhigh)
Llama 4 Maverick
Gemini 3 Flash- Gemini 3.1 Flash-Lite Preview
- Gemini 3.1 Pro Preview
Claude Opus 4.6 (max)- Claude 4.5 Haiku
- Claude Sonnet 4.6 (max)
Mistral Large 3
DeepSeek V3.2- Grok 4.1 Fast
Nova 2.0 Pro Preview (medium)
MiniMax-M2.5
NVIDIA Nemotron 3 Super- NVIDIA Nemotron 3 Nano
Kimi K2.5
K-EXAONE
MiMo-V2-Flash (Feb 2026)
K2 Think V2
Mi:dm K 2.5 Pro
GLM-5
Qwen3.5 397B A17B
Frequently Asked Questions
Common questions about Grok 4.20 Beta 0309 (Reasoning)
Grok 4.20 Beta 0309 (Reasoning) was released on March 10, 2026.
Grok 4.20 Beta 0309 (Reasoning) was created by xAI.
Grok 4.20 Beta 0309 (Reasoning) scores 48 on the Artificial Analysis Intelligence Index, placing it well above average among other reasoning models in a similar price tier (median: 28).
Grok 4.20 Beta 0309 (Reasoning) generates output at 265.1 tokens per second (based on the median across providers serving the model), which is well above average compared to other reasoning models in a similar price tier (median: 60.6 t/s).
Grok 4.20 Beta 0309 (Reasoning) has a time to first token (TTFT) of 9.18s (based on the median across providers serving the model), which is somewhat higher than average compared to other reasoning models in a similar price tier (median: 2.68s).
Grok 4.20 Beta 0309 (Reasoning) costs $2.00 per 1M input tokens (somewhat higher than average, median: $1.60) and $6.00 per 1M output tokens (better than average, median: $10.00), based on the median across providers serving the model.
Grok 4.20 Beta 0309 (Reasoning) costs $2.00 per 1M input tokens and $6.00 per 1M output tokens (based on the median across providers serving the model). For a blended rate (3:1 input to output ratio), this is $3.00 per 1M tokens. Pricing may vary by provider. Compare provider pricing
When evaluated on the Intelligence Index, Grok 4.20 Beta 0309 (Reasoning) generated 54M output tokens, which is somewhat higher than average compared to other reasoning models in a similar price tier (median: 13M).
Yes, Grok 4.20 Beta 0309 (Reasoning) is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.
Grok 4.20 Beta 0309 (Reasoning) supports text and image input.
Grok 4.20 Beta 0309 (Reasoning) supports text output.
Yes, Grok 4.20 Beta 0309 (Reasoning) supports image input and can analyze, describe, and answer questions about images.
Yes, Grok 4.20 Beta 0309 (Reasoning) is multimodal. It can process text and image input and generate text output.
Grok 4.20 Beta 0309 (Reasoning) has a context window of 2.0M tokens. This determines how much text and conversation history the model can process in a single request.
No, Grok 4.20 Beta 0309 (Reasoning) is proprietary. The model weights are not publicly available.
Grok 4.20 Beta 0309 (Reasoning) is a proprietary model and xAI has not disclosed the model size or parameter count.
Grok 4.20 Beta 0309 (Reasoning) achieves a score of 48 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.
Yes, Grok 4.20 Beta 0309 (Reasoning) is available via API through 1 provider. Compare API providers
Grok 4.20 Beta 0309 (Reasoning) is available through 1 API provider. Compare providers