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Model details

Tencent: Hunyuan A13B Instruct

Hunyuan-A13B-Instruct is a sparse Mixture-of-Experts chat model released by Tencent through its GitHub organization. Third-party listings describe it as carrying roughly eight billion total parameters while activating only about 1.3 billion at inference, a design that lets a modestly sized active pathway rival much larger dense models. This MoE shape is the foundation for its hybrid fast-thinking and slow-thinking modes, where lightweight responses and more deliberate reasoning can share the same underlying checkpoint.

Practically, the model is positioned for assistant-style workloads that benefit from long-context comprehension and tool use. A reseller listing highlights stable long-text understanding and claims agent capabilities verified by BFCL-v3 and τ-Bench, pointing at strong performance on function-calling and multi-step tasks. Through OpenAI-compatible gateways the model is exposed at a low per-token price tier, and the MoE design keeps active compute small, making it a reasonable fit for hosted agent pipelines, retrieval-heavy assistants, and latency-sensitive chat where deeper reasoning can be invoked on demand.

Kilo Gatewaytencent/hunyuan-a13b-instructhunyuan

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Provider
Kilo Gateway
Model key
tencent/hunyuan-a13b-instruct
Release date
Jul 8, 2025
Last updated
Jul 8, 2025
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.14
Output token cost
$0.57

Limits

Output tokens
117,964 tokens
Context window
131,072 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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CoverageBenchmark

A benchmark and evidence aggregator page dedicated to Tencent Hunyuan A13B Instruct reproduces vendor-reported numbers from the official Tencent Hunyuan-A13B-Instruct model card, including AIME24 at 87.3%, AIME25 at 76.8%, MATH at 94.3% (from a distinct evaluation table separate from a 72.35% base-model table), GPQA-Di Because the aggregator is redistributing the official Tencent model card rather than running independent evaluations, the numbers should be read as Tencent's own claims about Hunyuan A13B Instruct's reasoning performance rather than as third-party reproduced benchmarks. The page also separates a second MATH table (94.3

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