Grok 4.20 beta vs Grok 4.20 beta 0309 Reasoning

Grok 4.20 beta (xAI, 1,000,000-token context) versus Grok 4.20 beta 0309 Reasoning (xAI, 1,000,000-token context). Grok 4.20 beta is cheaper by 0% on a blended token mix. Across 1 public benchmark we tracked, Grok 4.20 beta wins 0 and Grok 4.20 beta 0309 Reasoning wins 1. Use the live calculator below to plug your real usage shape into both, then route the winner via Agent Command Center for shadow A/B without code changes.

Bottom line — Grok 4.20 beta vs Grok 4.20 beta 0309 Reasoning

Grok 4.20 beta and Grok 4.20 beta 0309 Reasoning are priced within 0% of each other, so cost alone is not the deciding factor. The comparison comes down to capabilities, context window, and benchmark performance on the specific task shape your workload demands.

For teams evaluating both models, the recommended path is a shadow A/B test: route production traffic through an OpenAI-compatible gateway, mirror a percentage to the candidate model, score both responses with an automated evaluator (faithfulness, tool-call correctness, latency), and compare cohort-level metrics over two weeks. Future AGI Agent Command Center supports this pattern with a single `base_url` change and built-in evaluators from the ai-evaluation SDK.

Side-by-side cost

Live workload comparison

Same workload run through both models. The cheaper one is highlighted.

3,000
01,000,000
400
0200,000
5,000
01,000,000
xAI
$723/mo
Input $1.25/M · Output $2.50/M
xAI
$723/mo
Input $1.25/M · Output $2.50/M
At this workload, Grok 4.20 beta 0309 Reasoning is 0% cheaper than Grok 4.20 beta — a savings of $0.000000/month ($0.000000/year).
Production recipe — Agent Command Center
strategy: cost-optimized
primary:
  model: grok-4-20-beta-0309-reasoning
  provider: xai
fallback:
  model: grok-4-20-beta
  provider: xai
shadow: { sample_rate: 0.05 }   # mirror 5% of traffic to compare quality live
Grok 4.20 beta
xAI
Grok 4.20 beta 0309 Reasoning
xAI
Input price $1.25/M $1.25/M
Output price $2.50/M $2.50/M
Context window 1,000,000 1,000,000
Max output 1,000,000 1,000,000
Function calling ✓ ✓
Vision ✓ ✓
Audio input — —
Reasoning ✓ ✓
Prompt caching ✓ ✓
Structured output ✓ ✓
Pricing verified Oct 22, 2026 Oct 22, 2026
Cheaper option
Larger context
1,000,000 tokens
More capabilities
5 of 6 capability flags advertised

Benchmark comparison

Side-by-side public benchmark scores. Greener bar = winner.

Arena ELO (coding)code
Grok 4.20 beta
1,511
Grok 4.20 beta 0309 Reasoning
—
Chatbot Arena ELOgeneral⚠ different settings
Grok 4.20 beta
1,472
Grok 4.20 beta 0309 Reasoning
1,477
Arena WebDevcode
Grok 4.20 beta
1,376
Grok 4.20 beta 0309 Reasoning
—
Arena Visionmultimodal
Grok 4.20 beta
1,255
Grok 4.20 beta 0309 Reasoning
—

Cost at scale: monthly spend at three usage volumes

Estimated monthly cost assuming 1,000 input + 200 output tokens per request — a realistic chat-agent shape. Adjust your own usage in the calculator at the top of this page for an exact number.

Scale Grok 4.20 beta Grok 4.20 beta 0309 Reasoning Delta
Startup
10K requests/day
$525 /mo $525 /mo —
Mid-market
100K requests/day
$5,250 /mo $5,250 /mo —
Enterprise
1M requests/day
$52,500 /mo $52,500 /mo —

At enterprise scale (1M requests/day), a difference of even ~10% in unit price compounds into thousands of dollars per month. Cached input pricing and batch tiers can shift this further — both are surfaced on each model's own page.

When to choose which

Picked from the data above — not vendor marketing. Match the rules to your workload, not the other way around.

Choose Grok 4.20 beta 0309 Reasoning

On arena-elo, Grok 4.20 beta 0309 Reasoning scores 5.0 points higher — if your workload pattern matches that benchmark's task shape, the gap is meaningful.

Benchmark winners — by the numbers

For each public benchmark that has scores for both models, the higher score and the size of the gap. Benchmarks are noisy — treat anything under a 2-point delta as effectively tied.

Benchmark Grok 4.20 beta Grok 4.20 beta 0309 Reasoning Winner Δ
arena-elo 1472.0 1477.0 Grok 4.20 beta 0309 Reasoning +5.0

How to A/B test Grok 4.20 beta vs Grok 4.20 beta 0309 Reasoning in production

If you're stuck between the two, run them side-by-side on real traffic. Four steps the Future AGI team uses internally:

  1. 1. Point your existing OpenAI SDK at https://gateway.futureagi.com/v1. No code change beyond base_url and a virtual key.
  2. 2. Mark Grok 4.20 beta primary, mirror 20% of traffic to Grok 4.20 beta 0309 Reasoning in shadow mode. Both responses are logged; only the primary is served to users.
  3. 3. Score every shadow response with an evaluator — faithfulness, tool-call correctness, response latency, cost. Built-in evaluators in ai-evaluation cover the common axes.
  4. 4. Compare cohort-level metrics after two weeks. Switch primary when the candidate wins on what matters to your workload — and stays within your latency budget.

Full walkthrough on the Agent Command Center page.

FAQ — Grok 4.20 beta vs Grok 4.20 beta 0309 Reasoning

What is the context window of Grok 4.20 beta versus Grok 4.20 beta 0309 Reasoning? ▾

Grok 4.20 beta supports up to 1,000,000 tokens of context. Grok 4.20 beta 0309 Reasoning supports up to 1,000,000 tokens. Grok 4.20 beta 0309 Reasoning has the larger window by a factor of 1.0x, which matters for long-document RAG, multi-turn agent sessions, and tasks that need to keep an entire codebase in working memory.

Do Grok 4.20 beta and Grok 4.20 beta 0309 Reasoning both support tool calling? ▾

Yes — both Grok 4.20 beta and Grok 4.20 beta 0309 Reasoning support native function calling. Both also support structured output via JSON schema, so an agent can be ported between them with the same tool definitions.

Which model supports prompt caching for cost reduction? ▾

Both Grok 4.20 beta and Grok 4.20 beta 0309 Reasoning support prompt caching. Cached input tokens are typically discounted 50–90% versus uncached input, depending on the provider. For agents with a stable system prompt + retrieval context, the cached pricing tier is the real unit economics number to track.

How do I A/B test Grok 4.20 beta against Grok 4.20 beta 0309 Reasoning in production? ▾

Route both through an OpenAI-compatible gateway like Future AGI Agent Command Center with shadow mode enabled. Send 100% of traffic to your primary model, mirror 10–20% to the candidate, score every response with an evaluator (faithfulness, tool-call correctness, response time), and compare cohort-level metrics for two weeks. Switch when the candidate wins on the metrics that matter to your workload and stays within your latency budget.