Intelligence
22
score
Grok 4.20 0309 v2 (Non-reasoning) scores 22 (estimated) on the Artificial Analysis Intelligence …
vs class avg: 17
xAI•Open weights•April 7, 2026
Grok 4.20 0309 v2
Intelligence, Performance & Price Analysis
Source:Artificial Analysis scrapeType:Open weights
Speed
171.5
output tokens/sec
Grok 4.20 0309 v2 (Non-reasoning) generates output at 171.5 tokens per second (based on xAI's API), …
Latency
0.56s
TTFT
Grok 4.20 0309 v2 (Non-reasoning) has a time to first token (TTFT) of 0. …
Input Price
$2.00
/ 1M tokens
Grok 4.20 0309 v2 (Non-reasoning) costs $2.00 per 1M input tokens (better than average, median: $1. …
Output Price
$6.00
/ 1M tokens
Grok 4.20 0309 v2 (Non-reasoning) costs $2.00 per 1M input tokens (better than average, median: $1. …
Decision Overview
Ethen's intelligence-driven routing assessment for this model
Overall verdict
Strong general-purpose model
Suitable for most production tasks, but high-volume or repetitive work should still be compared against cheaper routes.
Best for
- Code generation
- Content analysis
- Structured extraction
- Customer-facing chat
- Low-latency chat
- Interactive turn-taking
- High-value tasks where quality outweighs cost
Weak or unsuitable
- Extremely long-context tasks
- Ultra-low-latency requirements
- Routine high-volume generation
- Simple extraction or labeling
Routing recommendation
1
Lower-cost models for repetitive or high-volume work
2
Cache-backed reuse for repeated prompts
Cost pressure
Premium pricing — $2.00 / M input, $6.00 / M output. Use cheaper routes for repetitive or low-risk work.
Model-fit matrix
Use this model where capability pays for itself; route away where volume, latency, or budget dominate.
| Use case | Fit | Reason | Routing note |
|---|---|---|---|
| Complex reasoning & agentic workflows | Strong | Intelligence score 22 supports capable reasoning, but very hard tasks may benefit from higher-tier models. | Good for most complex tasks; consider a frontier model for the hardest 10%. |
| High-volume chat & customer-facing | Excellent | Output speed 171.5 tokens/sec and capable intelligence make this suitable for real-time chat at scale. | Ideal for interactive chat; enable caching for repeated queries. |
| Latency-sensitive applications | Excellent | TTFT 0.56s — among the lowest latencies, suitable for interactive latency-critical use cases. | Good first choice for real-time applications. |
| Cost-sensitive pipelines | Moderate | Output pricing at $6.00 is premium. Route high-volume simple tasks to cheaper alternatives. | Use only for high-value tasks; route simple queries to budget models. |
Cost pressure
HighPricing is premium — input $2.00, output $6.00. This model is expensive for high-volume or output-heavy workloads.
Cheaper substitutes
- Lower-cost models for repetitive or high-volume work
- Cache-backed reuse for repeated prompts
Route away when
- Output-heavy tasks
- High-frequency chat at scale
- Simple queries that cheaper models handle well
Highlights
Key benchmark results at a glance.
Intelligence
Intelligence position
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Grok 4.20 0309 v2 (Non-reasoning) scores 22 (estimated) on the Artificial Analysis Intelligence Index, placing it above average among other non-reasoning models in a similar price tier (median: 17).
Speed
Speed position
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Grok 4.20 0309 v2 (Non-reasoning) generates output at 171.5 tokens per second (based on xAI's API), which is well above average compared to other non-reasoning models in a similar price tier (median: 61.7 t/s).
Context, Cost & Pricing
Price/value position
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Pricing is premium — input $2.00, output $6.00. This model is expensive for high-volume or output-heavy workloads.
Intelligence & Quality
Benchmark scores and quality indices measuring model capability.
AA-Omniscience Index
AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Speed & Throughput
Output tokens per second and generation throughput.
Output Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Speed should be read together with latency and cost; fast output does not always mean better user-perceived performance.
Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Speed should be read together with latency and cost; fast output does not always mean better user-perceived performance.
Latency & Response Time
Time to first token and end-to-end response latency.
End-to-End Response Time
Seconds to output 500 tokens, including reasoning model 'thinking' time · Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Latency: Time To First Answer Token
Seconds to first answer token received · Accounts for reasoning model 'thinking' time · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Latency includes thinking / reasoning time when applicable. Lower is better for interactive use cases.
Context, Cost & Pricing
Context window size, cost per task, and token pricing.
Context Window
Context window: tokens limit · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Larger context windows enable complex multi-turn tasks but may increase latency and cost for long inputs.
Cost per Intelligence Index Task
Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Cost per Task
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Cost to Run Artificial Analysis Intelligence Index
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Pricing: Cache Hit, Input, and Output
Price (USD per M Tokens) · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Time per Intelligence Index Task
Weighted average decode time (minutes) per task; excludes TTFT and overhead time · Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Specifications
Technical Specifications
Grok 4.20 0309 v2 (Non-reasoning) scores 22 (estimated) on the Artificial Analysis Intelligence Index, placing it above average among other non-reasoning models in a similar price tier (median: 17). Grok 4.20 0309 v2 (Non-reasoning) generates output at 171.5 tokens per second (based on xAI's API), which is well above average compared to other non-reasoning models in a similar price tier (median: 61.7 t/s). Grok 4.20 0309 v2 (Non-reasoning) costs $2.00 per 1M input tokens (better than average, median: $1.88) and $6.00 per 1M output tokens (better than average, median: $7.75), based on xAI's API.
Grok 4.20 0309 v2
- Model type
- Open weights
- Reasoning
- No
- Input modalities
- Grok 4.20 0309 v2 (Non-reasoning) supports text and image input.
- Output modalities
- Grok 4.20 0309 v2 (Non-reasoning) supports text output.
- Context window
- Grok 4.20 0309 v2 (Non-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.
- Open weights / source
- No, Grok 4.20 0309 v2 (Non-reasoning) is proprietary. The model weights are not publicly available.
- Parameters
- Grok 4.20 0309 v2 (Non-reasoning) is a proprietary model and xAI has not disclosed the model size or parameter count.
- API availability
- Yes, Grok 4.20 0309 v2 (Non-reasoning) is available via API through 1 provider.
Methodology & Provenance
This page is rendered from the normalized profile and page JSON for Grok 4.20 0309 v2.
Benchmark values are preserved as normalized; only layout, disclosure ordering, and typography are adjusted for readability.
Source file: md/scrape/artificial_analysis_model_pages/artificialanalysis_ai__models__grok-4-20-non-reasoning__1d00d7145b.html · Canonical URL: https://artificialanalysis.ai/models/grok-4-20-non-reasoning
Normalized at: 2026-07-08T03:24:56+00:00 Technical specs, comparison summary, and FAQs are passed through from the normalized data without rewriting.
Visible FAQ answers and FAQ JSON-LD are emitted from the same normalized FAQ array, so structured data stays aligned with the rendered accordion.
Time per Intelligence Index Task: https://artificialanalysis.ai/models/grok-4-20-non-reasoning
Frequently Asked Questions
Grok 4.20 0309 v2 (Non-reasoning) was released on April 7, 2026.
Grok 4.20 0309 v2 (Non-reasoning) was created by xAI.
Grok 4.20 0309 v2 (Non-reasoning) scores 22 (estimated) on the Artificial Analysis Intelligence Index, placing it above average among other non-reasoning models in a similar price tier (median: 17).