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INF 34B Chat is an AI model released 2024 by infly, a leading organization in large language model research. Infly INF 34B — bilingual English/Chinese chat model strong at structured data analysis, table reasoning, and business Q&A. With 34B and a 128K tokens context window, INF 34B Chat is designed to excel across a range of demanding tasks — from software engineering and mathematical problem-solving to multilingual content generation and long-document analysis.

INF 34B Chat uses a dense transformer architecture with 34B of parameters, all of which are active for every input token. Dense architectures provide predictable, consistent behavior across diverse task types — there are no "cold" experts to warm up, and quality is uniform across prompts. infly's training pipeline combined large-scale pretraining on a large-scale multilingual pretraining dataset with supervised fine-tuning and alignment techniques (RLHF or DPO), producing INF 34B Chat's characteristic balance of capability, helpfulness, and safety.

As of 2026-10-16, INF 34B Chat by infly demonstrates measurable performance on standard AI evaluation benchmarks. On MMLU — which tests world knowledge across 57 academic subjects from elementary to professional level — it achieves 73.8%. For software engineering tasks, INF 34B Chat scores 68.3% on HumanEval, which tests ability to write correct functions from docstrings. These scores place INF 34B Chat — at 34B of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.

The primary strengths of INF 34B Chat are: Strong general-purpose performance at 34B scale; Long context support; Good instruction following. These make it particularly well-suited for General-purpose enterprise AI applications at 34B scale, Long-context document analysis. Users working on complex, multi-step problems benefit most from INF 34B Chat's ability to maintain coherence across long inputs and produce structured, verifiable outputs.

Like all current AI systems, INF 34B Chat has limitations: Less known than flagship models — smaller community support. For production deployments, validating outputs against authoritative sources — especially for domain-specific or time-sensitive information — remains best practice. infly continues to improve INF 34B Chat through ongoing research.

INF 34B Chat is available on LITHOVEX AI with a free account. Unlike direct API access — which requires billing setup, API key management, and per-token charges — LITHOVEX AI provides a seamless browser interface with no setup required, making INF 34B Chat accessible to students, researchers, developers, and early-stage teams globally.

As of 2026-10-16, INF 34B Chat by infly demonstrates measurable performance on standard AI evaluation benchmarks. On MMLU — which tests world knowledge across 57 academic subjects from elementary to professional level — it achieves 73.8%. For software engineering tasks, INF 34B Chat scores 68.3% on HumanEval, which tests ability to write correct functions from docstrings. These scores place INF 34B Chat — at 34B of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.

Dense transformer, 34B parameters, general-purpose instruction-tuned model

The training pipeline for INF 34B Chat involves multiple stages: large-scale pretraining on diverse multilingual text and code corpora to develop broad world knowledge, followed by supervised fine-tuning on instruction-response pairs, and alignment techniques such as RLHF or DPO. Each stage refines the model's helpfulness, accuracy, and safety. infly's research team — based in China — has optimized INF 34B Chat for the specific capability profile described above.

Inference efficiency: INF 34B Chat at 34B is designed to deliver quality outputs at practical serving speeds. Its 128K tokens context window enables processing entire documents, multi-file codebases, and extended conversation histories — particularly valuable for contract review, technical documentation analysis, and codebase-level AI assistance.

Getting started with INF 34B Chat on LITHOVEX AI takes under two minutes. Follow these steps:

For best results with INF 34B Chat: provide specific, context-rich prompts; include examples when generating code; specify output format when structure matters; break complex tasks into focused sub-questions.

Infly is an AI research organization focused on developing frontier-class open-weight language models. Their flagship models combine efficient architecture design with careful training on diverse multilingual corpora. Infly's models are released openly, making them accessible for research, commercial deployment, and community fine-tuning. The organization prioritizes making capable AI accessible to developers and researchers without requiring enterprise-level API subscriptions or compute budgets.

Founded: 2023, headquartered in China.

Visit the official infly website →

INF 34B Chat by infly competes in a field with several strong alternatives. Below is a detailed side-by-side comparison against commonly listed alternatives, using benchmark data and capability profiles in the catalog.

Both INF 34B Chat and the models above are available free on LITHOVEX AI — test them side by side on your real tasks before committing to a subscription with any provider.

INF 34B Chat is released under Custom license, which means you can download and run it on your own hardware. Below are the quickest ways to get started.

INF-34B Chat serves the mid-size model market where 7B lacks sufficient quality but 70B+ is too expensive. Teams globally building production AI who need better-than-7B quality without 70B+ costs find 34B models like this a practical compromise.

INF 34B Chat by infly has the following version history and notable updates:

For the complete changelog and latest release notes, visit the official infly model page.