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

Qwen3.8-Flash-NextvsGrok 4 Fast (Non-reasoning)

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

Alibaba

Qwen3.8-Flash-Next

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

Grok 4 Fast (Non-reasoning)

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

Winner by Category

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

Pricing Comparison

MetricQwen3.8-Flash-NextGrok 4 Fast (Non-reasoning)
Input ($/M tokens)$0.15$0.2
Output ($/M tokens)$0.47$0.5
Cost for 1M input + 100K output tokens:
Qwen3.8-Flash-Next$0.20
Grok 4 Fast (Non-reasoning)$0.25

Speed Comparison

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

Editorial Analysis

Verdict. Qwen3.8-Flash-Next wins the overall benchmark matchup 2–0 across 2 overlapping categories, but raw benchmark score is only one input to the decision.

Pricing. Both models sit in the budget bracket for output-token pricing. At 0.9× 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. Qwen3.8-Flash-Next is strongest on Coding Index (73.1), Intelligence Index (55.8). Grok 4 Fast (Non-reasoning) leads on Intelligence Index (16.6).

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

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-Flash-Next costs $11.55 ($139/year); Grok 4 Fast (Non-reasoning) costs $13.50 ($162/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Qwen3.8-Flash-Next ≈ $1.69/run, Grok 4 Fast (Non-reasoning) ≈ $2.00/run. At agent/realtime scale (200M input / 100M output per million requests): Qwen3.8-Flash-Next ≈ $77/run, Grok 4 Fast (Non-reasoning) ≈ $90/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
55.816.6
Coding Index
73.1
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Qwen3.8-Flash-Next2 wins
0 winsGrok 4 Fast (Non-reasoning)

Frequently Asked Questions

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

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 (Non-reasoning).

Which model performs better on benchmarks?

Qwen3.8-Flash-Next wins 2 out of 12 benchmarks compared to 0 for Grok 4 Fast (Non-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. Qwen3.8-Flash-Next also has lower time-to-first-token (2.78s vs —s).

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

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.