Model profile
SpaceXAI
New in 2026

Grok 4.3 (medium)

Grok 4.3 (medium) is a budget-priced text-first model from SpaceXAI with heavy runtime profile, partial context coverage, and the clearest fit around agent workflows / reasoning.

Best for: Agent workflows / ReasoningHeavy latencyN/A contextBudget pricing
Intelligence
36.9

Benchmark blend

Coding
N/A

Dev workflow signal

Context
N/A

N/A

Input Price
$1.25

Budget tier

Decision snapshot
50

Grok 4.3 (medium) currently reads as a budget text-first option with partially published context and a heavy runtime profile.

Overall profile
Use-case specific
Best for
Agent workflows / Reasoning
Latency tier
Heavy
Price tier
Budget
Source coverage
OpenRouterArtificial Analysis

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
36.9
37

General reasoning and benchmark headroom.

Limited
Speed
115 tok/s
41

TTFT 20.75s

Limited
Context
N/A
N/A

How much prompt and task state can stay in view.

Unavailable
Price
$1.25
86

$2.50 output / 1M

Efficient

Editorial Profile

Grok 4.3 (medium) in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Use-case specificCoding score N/AMath score N/A

The Grok 4.3 (medium) AI model by SpaceXAI.

Identity

SpaceXAI text-first profile

Positioning

Agent workflows / Reasoning with partially published context and heavy runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • The available source data suggests a balanced profile rather than one dominant edge.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Latency profile is better for deliberate runs than rapid back-and-forth chat.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

  • Context limits are only partially published, so long-session planning needs extra validation.

Best fit
  • Focused chat, retrieval-augmented flows, and narrower production tasks.

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Intelligence
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Context
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Input Price
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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
36.9
GPQA
89.0%
HLE
30.0%
Coding

Software implementation, debugging quality, and coding benchmark signal.

SciCode
44.6%

Extra benchmark cuts are not available for this category yet.

Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
83.3%
TAU2
91.2%
TerminalBench Hard
30.3%
LCR
68.3%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
N/A
Vision
Text-first
Price architecture
Input
per 1M input tokens
$1.25
Output
per 1M output tokens
$2.50
Blended
AA 3:1 mix
$1.56

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.