DeepSeek-V3 vs INF 34B Chat
Compare the listed model data for DeepSeek-V3 by DeepSeek and INF 34B Chat by infly. Benchmark and pricing records are not a controlled test and may change.
Data last updated: 2026-10-16. Verify current model details with each provider.
What the listed data says
DeepSeek-V3: 128K tokens; INF 34B Chat: 128K tokens. The listed context-window values are equal. DeepSeek-V3 is listed for coding, agentic workflows, long-context tasks; INF 34B Chat is listed for no specific capability flags. Shared catalog benchmark entries: MMLU: DeepSeek-V3 88.5%; INF 34B Chat 73.8%; HumanEval: DeepSeek-V3 89.9%; INF 34B Chat 68.3%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
Catalog source links
Use these model and provider links to verify current specifications, pricing, and availability.
Computed differences from catalog data
- The listed context windows are 128K tokens and 128K tokens; the larger is 1× the smaller.
- On shared numeric benchmark entries, MMLU: DeepSeek-V3 − INF 34B Chat = +14.7 percentage points (88.5% vs 73.8%); HumanEval: DeepSeek-V3 − INF 34B Chat = +21.6 percentage points (89.9% vs 68.3%).
- The first listed parameter quantities are 671B total (37B active via MoE) and 34B; the larger quantity is 19.74× the smaller. Total and active MoE parameters are not directly equivalent.
- A release-date gap cannot be calculated from the catalog values (DeepSeek-V3: December 2024; INF 34B Chat: 2024).
Cost example: 1M input and 1M output tokens
A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.
Choose DeepSeek-V3 if…
Choose DeepSeek-V3 when your task aligns with catalog-listed uses or strengths such as General-purpose coding and software development, Business document analysis, API building at high quality and low cost, Enterprise AI integration at scale.
Choose INF 34B Chat if…
Choose INF 34B Chat when your task aligns with catalog-listed uses or strengths such as General-purpose enterprise AI applications at 34B scale, Long-context document analysis, Strong general-purpose performance at 34B scale, Long context support.
DeepSeek-V3
DeepSeek flagship chat & code model — top-tier on coding benchmarks, long context tasks, and instruction following.
Parameters: 671B total (37B active via MoE)
Context: 128K tokens
Catalog pricing: MIT open source. DeepSeek API: $0.27/MTok input, $1.10/MTok output
INF 34B Chat
Infly INF 34B — bilingual English/Chinese chat model strong at structured data analysis, table reasoning, and business Q&A.
Parameters: 34B
Context: 128K tokens
Catalog pricing: Check Infly/HuggingFace for license terms
Feature Comparison — DeepSeek-V3 vs INF 34B Chat
| Specification | DeepSeek-V3 | INF 34B Chat |
|---|---|---|
| Provider | DeepSeek | infly |
| Parameters | 671B total (37B active via MoE) | 34B |
| Context window | 128K tokens | 128K tokens |
| Maximum output | Not listed | Not listed |
| Catalog pricing | MIT open source. DeepSeek API: $0.27/MTok input, $1.10/MTok output | Check Infly/HuggingFace for license terms |
| Listed input/output cost per 1M tokens | input $0.27, output $1.1 per 1M tokens | Separate numeric input/output rates not listed |
| License | MIT | Custom license |
| Coding support | Listed | Not listed |
| Reasoning support | Not listed | Not listed |
| Vision input | Not listed | Not listed |
| Multimodal | Not listed | Not listed |
| Open weights | Yes | Yes |
| Benchmark: MMLU | 88.5% | 73.8% |
| Benchmark: HumanEval | 89.9% | 68.3% |
Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.
Frequently Asked Questions
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Explore these models and related comparisons
Read the DeepSeek-V3 model profile and INF 34B Chat model profile, or browse the model directory.