Head to head · Open-weight models you run yourself · October 2026 research run
Kimi K3.1 Pro vs Ling-3.0-tiny
Ling-3.0-tiny scores 56.2 (C) on agent readiness against Kimi K3.1 Pro's 48.6 (D), and leads in 2 of 4 scored categories. Kimi K3.1 Pro leads on agent interface. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 4969 open weights comparisons
Which one, for what
Best for Operators with a multi-accelerator node who want Moonshot's newest open-weight model for coding and long agent sessions, and everyone else through an API
Ahead on
- Agent interface, 65 against 60
Watch for
1,561 GB of files, so it needs a node of eight large accelerators at least
Best for Agents on a laptop or small GPU that want a fast local model for tool calls and short reasoning, under MIT
Ahead on
- Reach, 95 against 40
- Documentation and upkeep, 56 against 51
Watch for
No inference provider is listed on the Hub and no inclusionAI API serves it
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Reach Ling-3.0-tiny +55
Kimi K3.1 Pro 40
Memory 0, the only build is Moonshot's 1,561 GB MXFP4 release, far above 256 GB. Runtimes 5, llama.cpp b12242 alone has the model code in a release, since vLLM's recipe needs 0.34.0 and SGLang's cookbook a branch. Builds 10, one precision. Terms 10, free commercial use below a model-as-a-service revenue threshold. Download 10, not gated. Hosted 5, Moonshot's API and Together serve it. 0 + 5 + 10 + 10 + 10 + 5 = 40.
Ling-3.0-tiny 95
Memory earns the full 30, since inclusionAI's own Q4_K_M GGUF is 4.8 GB, about 6 GB with a fifth added. Runtimes earn the full 25, from released Transformers, vLLM, SGLang and llama.cpp, and Ollama, whose v0.40.14 (2 November 2026) pins llama.cpp b11963 with the bailingmoe3 architecture (Ollama v0.40.7 of 20 October already pinned b11738, which has it). LM Studio has nothing. Builds earn 15 for FP8, INT4 and four GGUF precisions from inclusionAI. MIT with nothing added gives terms the full 15 and the ungated repositories give download the full 10. Hosted too scores 0, because the Hub's model page lists no inference provider and no inclusionAI or Ant Group API serving it was found.
Agent interface Kimi K3.1 Pro +5
Kimi K3.1 Pro 65
Chat template 10, the format is only code to run. Tool-calling format 10, the parser is named in the runtimes' recipes and the card doesn't say how tools are declared. Trained tool calling 20, several calls a turn on Kimi K3's tools channel. Structured output 5, named among linked guides without the how. Reasoning control 10, reasoning_effort per request. Context 10, 1M tokens. 10 + 10 + 20 + 5 + 10 + 10 = 65.
Ling-3.0-tiny 60
Chat template 20, a Jinja file in the repository. Tool-calling format 10, the format is only in the template and the card names the ling3 parser in commands without describing it, while SGLang uses another parser. Trained tool calling 20, several calls a turn and agentic results on the card. Structured output 0, not documented. Reasoning control 0, thinking turns off per request but the card doesn't say where the reasoning comes back. Context 10, 131,072 tokens native.
Documentation and upkeep Ling-3.0-tiny +5
Kimi K3.1 Pro 51
Model card 11, no limitations, languages or cut-off. Training data 5, one general sentence. Last change 20, a commit on 5 November 2026. Responsiveness 0, none of the 8 newest discussions has a reply from Moonshot. Version policy 5, Kimi K3 keeps its repository and no dated note was found. File health 10, the files agree. 11 + 5 + 20 + 0 + 5 + 10 = 51.
Ling-3.0-tiny 56
Model card 11, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 15, a data card with sources, size, cut-off and filtering. Last change 15, the newest commit is still the card change of 24 September 2026, 41 days before 4 November. Responsiveness 10, six of 16 discussions answered by an inclusionAI member, some. Version policy 5, a first release at this size. File health 0, the card's MTP recipe contradicts the files and a broken index size waits without a reply.
Score by category
| Category | Weight this run | Kimi K3.1 Pro | Ling-3.0-tiny | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 40 | 95 | Ling-3.0-tiny +55 |
| Risk | 20%20 | 50 | 50 | even |
| Agent interface | 10%10 | 65 | 60 | Kimi K3.1 Pro +5 |
| Documentation and upkeep | 10%10 | 51 | 56 | Ling-3.0-tiny +5 |
| Negative events | ≤15 | 0 | 0 | |
| Total | D 48.6/100 | C 56.2/100 |
Facts side by side
| Fact | Kimi K3.1 Pro | Ling-3.0-tiny |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Moonshot AI | inclusionAI (Ant Group) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Kimi K3.1 Pro License (modified MIT) | MIT |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-05 | 2026-08-31 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | none | 2.8/5 (4) |
How the scores have moved
Kimi K3.1 Pro
No score change since it was listed.
Verdicts
Kimi K3.1 Pro
Moonshot's newest flagship, eight days old when read, for operators with a rack. Only llama.cpp has its model code in a release, with vLLM and SGLang support still on a release candidate and a branch. The licence is permissive below a revenue threshold, and Moonshot hasn't answered a discussion on the repository yet.
Ling-3.0-tiny
A small, quick hybrid reasoning model for local agent work, tool calls and coding, under MIT. It runs in about 6 GB from inclusionAI's 4-bit GGUF in released Transformers, vLLM, SGLang, llama.cpp and Ollama, with no host. The risks are a card that doesn't match the files in places, a vLLM route running repository code, and no safety results.
Before you call either
Kimi K3.1 Pro
- Use Moonshot's API or Together unless you have a node of eight B300-class accelerators
- With vLLM use 0.34.0 or later and the recipe's flags,
--tool-call-parser kimi_k3 --reasoning-parser kimi_k3 - Pass the whole assistant message back in later turns, reasoning_content and tool_calls included, as the card requires
- Set
reasoning_effortto low, high or max per request. Max is the default and thinking can't be turned off - Kimi K3's model code doesn't load it, because the attention layers changed
- Validate JSON output yourself, since the card doesn't document structured output for the weights
Ling-3.0-tiny
- Start it with
llama-server -hf inclusionAI/Ling-3.0-tiny-GGUF:Q4_K_M --jinja -c 32768, which needs llama.cpp b11772 or a recent release with bailingmoe3 - With vLLM 0.32.0,
vllm serve inclusionAI/Ling-3.0-tiny --trust-remote-code --enable-prefix-caching --mamba-cache-mode align --enable-auto-tool-choice --tool-call-parser ling3 --reasoning-parser ling3, which runs the repository's config code - With SGLang 0.5.22, its cookbook uses
--reasoning-parser deepseek-r1 --tool-call-parser glm45for this model, and drop the card's NEXTN flags since tiny has no MTP layer - Thinking is on by default, pass
chat_template_kwargswithenable_thinkingfalse for short tasks - Sampling per the card is temperature 1.0, top_p 0.95 and top_k 20
- The template keeps earlier reasoning in the prompt, which grows long agent sessions
- Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented
- For a guardrail, inclusionAI's Ling-3.0-tiny-singprobe scores intent, unsafe output and hallucination per token, but only through SGLang and vLLM integration branches
Questions
Which is better for AI agents, Kimi K3.1 Pro or Ling-3.0-tiny?
Ling-3.0-tiny scores 56.2 (C) on agent readiness against Kimi K3.1 Pro's 48.6 (D), and leads in 2 of 4 scored categories. Kimi K3.1 Pro leads on agent interface.
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Machine-readable
- This page as Markdown
/compare/kimi-k3-1-pro-vs-ling-3-0-tiny.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/kimi-k3-1-pro.json·/api/v1/tools/ling-3-0-tiny.json - From a terminal
anchor compare kimi-k3-1-pro ling-3-0-tiny(the CLI) - Over MCP
compare_tools {"a": "kimi-k3-1-pro", "b": "ling-3-0-tiny"}at/mcp, no key