Compare/Grok 4 Fast (Reasoning) vs Qwen3.8-Flash-Next

Grok 4 Fast (Reasoning)vsQwen3.8-Flash-Next

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

SpaceXAI

Grok 4 Fast (Reasoning)

Input
$0.2/M
Output
$0.5/M
Speed
TTFT
Alibaba

Qwen3.8-Flash-Next

Input
$0.15/M
Output
$0.47/M
Speed
85 tok/s
TTFT
2.78s

Winner by Category

Cheaper
Qwen3.8-Flash-Next
Faster (tok/s)
Qwen3.8-Flash-Next
Lower Latency
Qwen3.8-Flash-Next
Benchmarks (0-2)
Qwen3.8-Flash-Next

Pricing Comparison

MetricGrok 4 Fast (Reasoning)Qwen3.8-Flash-Next
Input ($/M tokens)$0.2$0.15
Output ($/M tokens)$0.5$0.47
Cost for 1M input + 100K output tokens:
Grok 4 Fast (Reasoning)$0.25
Qwen3.8-Flash-Next$0.20

Speed Comparison

Output Speed (tokens/s) — higher is better
Grok 4 Fast (Reasoning)
Qwen3.8-Flash-Next
85 tok/s
Time to First Token (seconds) — lower is better
Grok 4 Fast (Reasoning)
Qwen3.8-Flash-Next
2.78s

Editorial Analysis

Verdict. Qwen3.8-Flash-Next takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.

Pricing. Both models sit in the budget bracket for output-token pricing. At 1.1× the per-million-token cost, Qwen3.8-Flash-Next is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Qwen3.8-Flash-Next makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Grok 4 Fast (Reasoning) is strongest on Intelligence Index (27.9). Qwen3.8-Flash-Next leads on Coding Index (73.1), Intelligence Index (55.8).

Speed. Speed data is incomplete for this pair; benchmark and price should decide.

Provider. SpaceXAI and Alibaba sell to overlapping but distinct developer audiences: SpaceXAI tends to ship frontier reasoning models with premium positioning, while Alibaba 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): Grok 4 Fast (Reasoning) costs $13.50 ($162/year); Qwen3.8-Flash-Next costs $11.55 ($139/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Grok 4 Fast (Reasoning) ≈ $2.00/run, Qwen3.8-Flash-Next ≈ $1.69/run. At agent/realtime scale (200M input / 100M output per million requests): Grok 4 Fast (Reasoning) ≈ $90/run, Qwen3.8-Flash-Next ≈ $77/run. Qwen3.8-Flash-Next becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.

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.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
27.955.8
Coding Index
73.1
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Grok 4 Fast (Reasoning)0 wins
2 winsQwen3.8-Flash-Next

Frequently Asked Questions

Which is cheaper, Grok 4 Fast (Reasoning) or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next is cheaper overall. Its blended price (3:1 input/output ratio) is $0.23/M tokens vs $0.28/M for Grok 4 Fast (Reasoning).

Which model performs better on benchmarks?

Qwen3.8-Flash-Next wins 2 out of 12 benchmarks compared to 0 for Grok 4 Fast (Reasoning). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Qwen3.8-Flash-Next generates tokens faster at 85 tok/s vs — tok/s. However, Qwen3.8-Flash-Next has lower time-to-first-token (2.78s vs —s).

When should I use Grok 4 Fast (Reasoning) vs Qwen3.8-Flash-Next?

Choose based on your priorities: Qwen3.8-Flash-Next for lower cost, Qwen3.8-Flash-Next for stronger benchmark performance, and Qwen3.8-Flash-Next for faster generation. For latency-sensitive apps, check the TTFT comparison above.