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Model details

Qwen3 8B

Qwen3 8B belongs to Alibaba's Qwen3 generation of large language models, which the family documentation describes as an evolution over Qwen2.5 with denser and higher-quality pre-training, architectural refinements, and a three-stage training pipeline intended to lift general knowledge, reasoning, and long-context comprehension. Within that lineup, the 8B-class checkpoint is positioned as a mid-sized dense option aimed at developers who want capable language understanding and generation without the resource demands of larger Qwen3 variants.

Practical fit centers on text-in, text-out language tasks, with the model's open-weight availability making it adaptable to local deployment, fine-tuning, and integration into pipelines that need reasoning or tool-calling behavior. Because the supplied sources document only the Base pre-training variant rather than the post-trained Qwen3-8B checkpoint itself, detailed numeric claims about the instruct model's parameters, context behavior, and benchmark performance are not asserted here; the qualitative picture is of a compact, open Qwen3-family model intended for general language work and downstream customization.

PioneerQwen/Qwen3-8Bqwen

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Provider
Pioneer
Model key
Qwen/Qwen3-8B
Release date
Mar 31, 2025
Last updated
Apr 28, 2025
Knowledge cutoff
2025-03-31
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.20
Output token cost
$0.20

Limits

Output tokens
40,960 tokens
Context window
40,960 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about Qwen3 8B

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CoverageBenchmark

BenchGecko's profile for Qwen3 8B documents Alibaba's 8.2-billion-parameter dense causal language model from the Qwen3 series, released April 2025 under an open-source license with a 131K-token context window. The page reports input pricing at $0.12 per million tokens and output pricing at $0.46 per million tokens, alo The profile lists six benchmark results for Qwen3 8B: IFEval 85.6%, MMLU-Pro 72.1%, AIME2025 66.2%, LiveCodeBench v6 50.1, GPQA-Diamond 59.7, and HLE 5.5. BenchGecko notes the model supports seamless switching between a thinking mode for math/reasoning and an efficient dialogue mode, and contextualizes it within the br

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