Compare/Qwen3 VL 8B Instruct vs Celeris-1

Qwen3 VL 8B InstructvsCeleris-1

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

Alibaba

Qwen3 VL 8B Instruct

Input
$0.18/M
Output
$0.7/M
Speed
107 tok/s
TTFT
2.26s
Celeris

Celeris-1

Input
$0.2/M
Output
$0.7/M
Speed
1484 tok/s
TTFT
0.58s

Winner by Category

Cheaper
Qwen3 VL 8B Instruct
Faster (tok/s)
Celeris-1
Lower Latency
Celeris-1
Benchmarks (0-2)
Celeris-1

Pricing Comparison

MetricQwen3 VL 8B InstructCeleris-1
Input ($/M tokens)$0.18$0.2
Output ($/M tokens)$0.7$0.7
Cost for 1M input + 100K output tokens:
Qwen3 VL 8B Instruct$0.25
Celeris-1$0.27

Speed Comparison

Output Speed (tokens/s) — higher is better
Qwen3 VL 8B Instruct
107 tok/s
Celeris-1
1484 tok/s
Time to First Token (seconds) — lower is better
Qwen3 VL 8B Instruct
2.26s
Celeris-1
0.58s

Editorial Analysis

Verdict. Celeris-1 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 1.0× the per-million-token cost, Celeris-1 is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Celeris-1 makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Qwen3 VL 8B Instruct is strongest on Intelligence Index (8.2). Celeris-1 leads on Coding Index (14.4), Intelligence Index (12.4).

Speed. On throughput, Celeris-1 generates tokens at 1484 tok/s versus 107 tok/s — about 93% faster. On time-to-first-token, Celeris-1 responds in 580ms vs 2260ms, which matters most for chat-style UIs.

Provider. Alibaba and Celeris sell to overlapping but distinct developer audiences: Alibaba tends to ship frontier reasoning models with premium positioning, while Celeris 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 VL 8B Instruct costs $15.90 ($191/year); Celeris-1 costs $16.50 ($198/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Qwen3 VL 8B Instruct ≈ $2.30/run, Celeris-1 ≈ $2.40/run. At agent/realtime scale (200M input / 100M output per million requests): Qwen3 VL 8B Instruct ≈ $106/run, Celeris-1 ≈ $110/run. Qwen3 VL 8B Instruct 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.

Head-to-head deltas

  • On throughput, Celeris-1 is 13.82× faster (1484 tok/s vs 107 tok/s). For streaming chat or real-time agents this alone often flips the recommendation.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
8.212.4
Coding Index
14.4
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Qwen3 VL 8B Instruct0 wins
2 winsCeleris-1

Frequently Asked Questions

Which is cheaper, Qwen3 VL 8B Instruct or Celeris-1?

Qwen3 VL 8B Instruct is cheaper overall. Its blended price (3:1 input/output ratio) is $0.31/M tokens vs $0.33/M for Celeris-1.

Which model performs better on benchmarks?

Celeris-1 wins 2 out of 12 benchmarks compared to 0 for Qwen3 VL 8B Instruct. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Celeris-1 generates tokens faster at 1484 tok/s vs 107 tok/s. However, Celeris-1 has lower time-to-first-token (0.58s vs 2.26s).

When should I use Qwen3 VL 8B Instruct vs Celeris-1?

Choose based on your priorities: Qwen3 VL 8B Instruct for lower cost, Celeris-1 for stronger benchmark performance, and Celeris-1 for faster generation. For latency-sensitive apps, check the TTFT comparison above.