Head to head · Open-weight models you run yourself · October 2026 research run
InternVL3.5-GPT-OSS-20B-A4B-Preview vs Kimi K3.1 Pro
InternVL3.5-GPT-OSS-20B-A4B-Preview scores 53.2 (D) 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 and documentation and upkeep. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 6359 open weights comparisons
Which one, for what
InternVL3.5-GPT-OSS-20B-A4B-Preview D
Best for Agents with 64 GB to spare that want an Apache-licensed image and video reader with optional thinking and can live with a stale preview.
Ahead on
- Reach, 65 against 40
- Risk, 55 against 50
Watch for
No quantised build from OpenGVLab, so about 51 GB at BF16
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 45
- Documentation and upkeep, 51 against 28
Watch for
1,561 GB of files, so it needs a node of eight large accelerators at least
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 InternVL3.5-GPT-OSS-20B-A4B-Preview +25
InternVL3.5-GPT-OSS-20B-A4B-Preview 65
Memory 15 of 30, the only builds are BF16 at 42.5 GB by the repository's safetensors index, or 51 GB with a fifth added, which fits 64 GB. Runtimes 25, Transformers and vLLM load this repository, and SGLang, llama.cpp and Ollama (through llama.cpp b11963, which Ollama v0.40.14 pins) run the same weights in their GitHub format. Builds 0, OpenGVLab publishes no quantised build. Terms 15, Apache 2.0 with nothing added by the bases. Download 10, not gated. Hosted 0, no provider serves it.
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.
Documentation and upkeep Kimi K3.1 Pro +23
InternVL3.5-GPT-OSS-20B-A4B-Preview 28
Model card 8 of 20, the family card misses limitations, context, languages and a cut-off. Training data 5, described without a cut-off. Last change 0, the last commit to either repository is 8 September 2025 and to OpenGVLab's reference code 22 September 2025, over a year before 4 November 2026. Responsiveness 10, OpenGVLab answered 3 of 8 questions across the two repositories, none since September 2025. Version policy 5, a first release. File health 0, the template uses markers the tokenizer doesn't have and contradicts the twin's template, and the card names the wrong language model in its licence line.
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.
Agent interface Kimi K3.1 Pro +20
InternVL3.5-GPT-OSS-20B-A4B-Preview 45
Chat template 20, a Jinja file in the repository, though it doesn't match the tokenizer. Tool-calling format 10 of 25, only the twin's inherited harmony template mentions tools. Trained tool calling 0, no evidence it was trained to call tools. Structured output 0. Reasoning control 10, a system prompt turns thinking on and the card says the reasoning comes back in think tags. Context 5, trained at 32K tokens.
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.
Risk InternVL3.5-GPT-OSS-20B-A4B-Preview +5
InternVL3.5-GPT-OSS-20B-A4B-Preview 55
File safety 25, safetensors only and no code in the repository. Provenance 15, the files are in the OpenGVLab organisation its GitHub links, with a checksum on every file. Safety evaluation 0 and agent guidance 0, nothing published. Licence risk 15, Apache 2.0 over Apache and MIT bases, with gpt-oss's usage policy asking only for lawful use. Security programme 0, no policy, security.txt or advisories.
Kimi K3.1 Pro 50
File safety 15, safetensors only, less 10 for remote code and prompts built by the repository's script. Provenance 15, Moonshot's own organisation with a hash on every file. Safety evaluation 10, Moonshot's own cyber benchmark results and nobody else's yet. Agent guidance 0, none on the card. Licence risk 10, the revenue threshold. Security programme 0, no way to report a flaw found. 15 + 15 + 10 + 0 + 10 + 0 = 50.
Score by category
| Category | Weight this run | InternVL3.5-GPT-OSS-20B-A4B-Preview | Kimi K3.1 Pro | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 65 | 40 | InternVL3.5-GPT-OSS-20B-A4B-Preview +25 |
| Risk | 20%20 | 55 | 50 | InternVL3.5-GPT-OSS-20B-A4B-Preview +5 |
| Agent interface | 10%10 | 45 | 65 | Kimi K3.1 Pro +20 |
| Documentation and upkeep | 10%10 | 28 | 51 | Kimi K3.1 Pro +23 |
| Negative events | ≤15 | 0 | 0 | |
| Total | D 53.2/100 | D 48.6/100 |
Facts side by side
| Fact | InternVL3.5-GPT-OSS-20B-A4B-Preview | Kimi K3.1 Pro |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | OpenGVLab (Shanghai AI Laboratory) | Moonshot AI |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0; a merge of openai/gpt-oss-20b (Apache 2.0 with OpenAI's usage policy) and OpenGVLab/InternViT-300M-448px-V2_5 (MIT) | Kimi K3.1 Pro License (modified MIT) |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2025-09-08 | 2026-11-05 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 1.8/5 (4) | none |
How the scores have moved
Kimi K3.1 Pro
No score change since it was listed.
Verdicts
InternVL3.5-GPT-OSS-20B-A4B-Preview
An image and video reader on gpt-oss-20b with an optional thinking mode, a preview untouched for over a year. It needs about 51 GB in BF16, since OpenGVLab publishes no quantised build, and runs in Transformers and vLLM. The main risk is a chat template in the Transformers-format repository that doesn't match its tokenizer, with no safety results.
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.
Before you call either
InternVL3.5-GPT-OSS-20B-A4B-Preview
- Serve with
vllm serve OpenGVLab/InternVL3_5-GPT-OSS-20B-A4B-Preview-HF --max-model-len 32768, which is our command; the card gives none for vLLM - Check the rendered prompt before relying on it, since the shipped template's <|im_start|> markers aren't tokens in the gpt-oss tokenizer; the GitHub-format repository's harmony template is the alternative
- Use Transformers 4.55.0 or later, as the card requires for this size
- For thinking, send the card's thinking system prompt and parse the reasoning out of the <think> tags, with temperature 0.6 and sampling on as the card advises
- Keep inputs within 32K tokens, the length it was trained at, whatever the config says
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
Questions
Which is better for AI agents, InternVL3.5-GPT-OSS-20B-A4B-Preview or Kimi K3.1 Pro?
InternVL3.5-GPT-OSS-20B-A4B-Preview scores 53.2 (D) 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 and documentation and upkeep.
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- Kimi K3.1 Pro vs Qwopus3.8-27B-Flash-V2
- Kimi K3.1 Pro vs Recursive Flint
- Kimi K3.1 Pro vs Ripple-65B Preview
- Kimi K3.1 Pro vs SenseNova-Loop-9B-Preview
- Kimi K3.1 Pro vs SmolLM3-3B
- Kimi K3.1 Pro vs Spark-X2.6-4B
- Kimi K3.1 Pro vs Step 3.7 Flash
- Kimi K3.1 Pro vs Swift 1.5 Qwen3.8-27B
- Kimi K3.1 Pro vs Swift 1.5 Qwen3.8-Flash-Next
- Kimi K3.1 Pro vs ThinkingCap (Qwen3.8 27B)
- Kimi K3.1 Pro vs Baidu Unlimited-OCR-2
- Kimi K3.1 Pro vs WeVisOne-VL-2B
- Kimi K3.1 Pro vs WeVisOne-VL-4B
- Kimi K3.1 Pro vs ZAYA1-8B
- Kimi K3 vs Kimi K3.1 Pro
Machine-readable
- This page as Markdown
/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-kimi-k3-1-pro.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/internvl3-5-gpt-oss-20b-a4b-preview.json·/api/v1/tools/kimi-k3-1-pro.json - From a terminal
anchor compare internvl3-5-gpt-oss-20b-a4b-preview kimi-k3-1-pro(the CLI) - Over MCP
compare_tools {"a": "internvl3-5-gpt-oss-20b-a4b-preview", "b": "kimi-k3-1-pro"}at/mcp, no key