Compare/Qwen3.8 Max vs Grok 4.5 (high)

Qwen3.8 MaxvsGrok 4.5 (high)

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Alibaba

Qwen3.8 Max

Input
$2/M
Output
$6/M
Speed
39 tok/s
TTFT
2.50s
SpaceXAI

Grok 4.5 (high)

Input
$2/M
Output
$6/M
Speed
56 tok/s
TTFT
8.57s

Winner by Category

Cheaper
Tie
Faster (tok/s)
Grok 4.5 (high)
Lower Latency
Qwen3.8 Max
Benchmarks (1-1)
Tie

Pricing Comparison

MetricQwen3.8 MaxGrok 4.5 (high)
Input ($/M tokens)$2$2
Output ($/M tokens)$6$6
Cost for 1M input + 100K output tokens:
Qwen3.8 Max$2.60
Grok 4.5 (high)$2.60

Speed Comparison

Output Speed (tokens/s) — higher is better
Qwen3.8 Max
39 tok/s
Grok 4.5 (high)
56 tok/s
Time to First Token (seconds) — lower is better
Qwen3.8 Max
2.50s
Grok 4.5 (high)
8.57s

Editorial Analysis

Verdict. Qwen3.8 Max and Grok 4.5 (high) split the benchmark comparison evenly at 1–1. The tiebreaker here is price, speed, and what you actually run them on.

Pricing. Both models sit in the mid-tier bracket for output-token pricing. At 1.0× the per-million-token cost, Grok 4.5 (high) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Grok 4.5 (high) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Qwen3.8 Max is strongest on Coding Index (71.8), Intelligence Index (58.1). Grok 4.5 (high) leads on Coding Index (72.4), Intelligence Index (55.8).

Speed. On throughput, Grok 4.5 (high) generates tokens at 56 tok/s versus 39 tok/s — about 31% faster. On time-to-first-token, Qwen3.8 Max responds in 2500ms vs 8570ms, which matters most for chat-style UIs.

Provider. Alibaba and SpaceXAI sell to overlapping but distinct developer audiences: Alibaba tends to ship frontier reasoning models with premium positioning, while SpaceXAI often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.

Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): Qwen3.8 Max costs $150.00 ($1800/year); Grok 4.5 (high) costs $150.00 ($1800/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Qwen3.8 Max ≈ $22.00/run, Grok 4.5 (high) ≈ $22.00/run. At agent/realtime scale (200M input / 100M output per million requests): Qwen3.8 Max ≈ $1000/run, Grok 4.5 (high) ≈ $1000/run.

Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.

Head-to-head deltas

  • Benchmark wins tie exactly at 1–1. The tiebreaker on raw benchmark parity will be price, speed, or capability coverage.
  • Aggregate benchmark score (sum across 12 categories, capped at 100): Qwen3.8 Max = 130, Grok 4.5 (high) = 128. Within 15% — effectively equivalent if both meet the threshold your product requires.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
58.155.8
Coding Index
71.872.4
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Qwen3.8 Max1 wins
1 winsGrok 4.5 (high)

Frequently Asked Questions

Which is cheaper, Qwen3.8 Max or Grok 4.5 (high)?

Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.

Which model performs better on benchmarks?

It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Grok 4.5 (high) generates tokens faster at 56 tok/s vs 39 tok/s. Qwen3.8 Max also has lower time-to-first-token (2.50s vs 8.57s).

When should I use Qwen3.8 Max vs Grok 4.5 (high)?

Choose based on your priorities: both are similarly priced, both perform similarly on benchmarks, and Grok 4.5 (high) for faster generation. For latency-sensitive apps, check the TTFT comparison above.