Head to head · Open-weight models you run yourself · October 2026 research run
Kimi K3.1 Pro vs MiniCPM-V 4.7 1B
MiniCPM-V 4.7 1B scores 61 (C) on agent readiness against Kimi K3.1 Pro's 48.6 (D), and leads in 3 of 4 scored categories. 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
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
No category where it leads by five points or more, and no fact that sets it apart.
Watch for
1,561 GB of files, so it needs a node of eight large accelerators at least
Best for Agents that need a cheap local model to read screenshots, photos and short video on a phone, a laptop or beside a bigger model
Ahead on
- Reach, 95 against 40
- Risk, 55 against 50
- Agent interface, 70 against 65
Watch for
No limitations section, safety results, agent-use guidance or security contact
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 MiniCPM-V 4.7 1B +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.
MiniCPM-V 4.7 1B 95
Memory 30, OpenBMB's own IQ4_XS GGUF is 0.64 GB, 1.54 GB with the 0.90 GB vision projector, and 1.54 GB × 1.2 = 1.9 GB, which fits 16 GB with room to spare. Runtimes 25, MiniCPMV4_7ForConditionalGeneration in vLLM's registry at v0.33.0, the minicpmv4_7 model type in SGLang's minicpmv.py at v0.5.23, the minicpmv4_7 model in Transformers at v5.22.2, a MiniCPM-V 4.7 guide and conversion code in llama.cpp at b12242, and an openbmb/minicpm-v4.7:1b tag in OpenBMB's namespace on Ollama, read as the 35B-A3B listing's is. Builds 15, OpenBMB publishes AWQ, GPTQ and int4 safetensors builds and a GGUF repository from IQ3_XS to F16, so quantised builds at two precisions or more. Terms 15, Apache 2.0 in the card's metadata and as the LICENSE of OpenBMB's MiniCPM-V repository, an OSI licence. Download 10, gated is false on the main repository and on the GGUF, AWQ, GPTQ and int4 repositories, so the files download with no account or terms. Hosted 0, Hugging Face lists no inference provider for the model (an empty provider mapping on 10 November 2026), and no provider's own list was read. 30 + 25 + 15 + 15 + 10 + 0 = 95.
Risk MiniCPM-V 4.7 1B +5
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.
MiniCPM-V 4.7 1B 55
File safety 25, safetensors in the main repository and the AWQ, GPTQ and int4 builds, GGUF in the GGUF build, with no .bin, .pt, .pth or .py files in the main repository. Provenance 15, files in the openbmb organisation that OpenBMB's GitHub README links to (10), with a SHA-256 for both large files in the main repository (5). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or disclaimer section, and no prompt-injection guidance, instruction hierarchy or statement of trained refusals. Licence risk 15, Apache 2.0 has no use policy, field-of-use limit, threshold or change clause, nothing is added on the card, and the LICENSE in OpenBMB's GitHub repository resolved on 10 November 2026. Security programme 0, no SECURITY.md in OpenBMB/MiniCPM-V and no security.txt on openbmb.cn (both 404 on 10 November 2026), and no advisories found. 25 + 15 + 0 + 0 + 15 + 0 = 55.
Agent interface MiniCPM-V 4.7 1B +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.
MiniCPM-V 4.7 1B 70
Chat template 20, chat_template.jinja in the repository, 7,249 characters. Tool-calling format 10, the card shows tools declared in the OpenAI tools array in a request to Transformers' server, but not how a call comes back, and names no parser for vLLM or SGLang. Trained tool calling 20, the template loops over tool_calls, so it renders several calls in one assistant turn, and the card gives a tool-calling request as a supported use. Structured output 0, Neither JSON nor JSON Schema output is documented or claimed for the model on the card. Reasoning control 10, the card passes enable_thinking per request in its examples, the template has been off by default since 19 October 2026, and the GGUF repository keeps thinking builds in their own folder. Context 10, 262,144 tokens, max_position_embeddings in the text config. 20 + 10 + 20 + 0 + 10 + 10 = 70.
Score by category
| Category | Weight this run | Kimi K3.1 Pro | MiniCPM-V 4.7 1B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 40 | 95 | MiniCPM-V 4.7 1B +55 |
| Risk | 20%20 | 50 | 55 | MiniCPM-V 4.7 1B +5 |
| Agent interface | 10%10 | 65 | 70 | MiniCPM-V 4.7 1B +5 |
| Documentation and upkeep | 10%10 | 51 | 48 | Kimi K3.1 Pro +3 |
| Negative events | ≤15 | 0 | 0 | |
| Total | D 48.6/100 | C 61/100 |
Facts side by side
| Fact | Kimi K3.1 Pro | MiniCPM-V 4.7 1B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Moonshot AI | OpenBMB |
| 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) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-05 | 2026-10-30 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
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.
MiniCPM-V 4.7 1B
A vision-language cousin small enough for a phone, under plain Apache 2.0, that every runtime we count can load. The projector is bigger than the language model, so plan for about 2 GB. The card says nothing about limits or training data and doesn't show how a tool call comes back.
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
MiniCPM-V 4.7 1B
- Start it with
llama-server -hf openbmb/MiniCPM-V-4.7-1B-gguf:Q4_K_M --jinja, orollama run openbmb/minicpm-v4.7:1b - For image input in llama.cpp add
mmproj-model-f16.gguf, or the smaller 4x projector - The GGUF files at the repository root have thinking off. Use the files in
thinking/when you want the trace - Use temperature 0.7, top_p 0.95 and top_k 100 in instruct mode, as the card recommends
- Check tool calls in your runtime first, since the card names no parser
- Validate JSON output yourself, since structured output isn't documented
Questions
Which is better for AI agents, Kimi K3.1 Pro or MiniCPM-V 4.7 1B?
MiniCPM-V 4.7 1B scores 61 (C) on agent readiness against Kimi K3.1 Pro's 48.6 (D), and leads in 3 of 4 scored categories.
Other comparisons with Kimi K3.1 Pro or MiniCPM-V 4.7 1B
- Agents-A1-4B vs Kimi K3.1 Pro
- Agents-A1-4B vs MiniCPM-V 4.7 1B
- Apertus v1.5 8B vs Kimi K3.1 Pro
- Apertus v1.5 8B vs MiniCPM-V 4.7 1B
- Apodex-1.1-mini vs Kimi K3.1 Pro
- Apodex-1.1-mini vs MiniCPM-V 4.7 1B
- Arete-27B vs Kimi K3.1 Pro
- Arete-27B vs MiniCPM-V 4.7 1B
- BigBang-v1 vs Kimi K3.1 Pro
- BigBang-v1 vs MiniCPM-V 4.7 1B
- Carbon-X vs Kimi K3.1 Pro
- Carbon-X vs MiniCPM-V 4.7 1B
- Cola2 vs Kimi K3.1 Pro
- Cola2 vs MiniCPM-V 4.7 1B
- Cosmos-Reason2-2B vs Kimi K3.1 Pro
- Cosmos-Reason2-2B vs MiniCPM-V 4.7 1B
- Darwin-36B-Opus vs Kimi K3.1 Pro
- Darwin-36B-Opus vs MiniCPM-V 4.7 1B
- DeepSeek-V3.2 vs Kimi K3.1 Pro
- DeepSeek-V3.2 vs MiniCPM-V 4.7 1B
- DeepSeek V4.1 Flash vs Kimi K3.1 Pro
- DeepSeek V4.1 Flash vs MiniCPM-V 4.7 1B
- DeepSeek-V4-Flash-0731 vs Kimi K3.1 Pro
- DeepSeek-V4-Flash-0731 vs MiniCPM-V 4.7 1B
- Devstral Small 2 vs Kimi K3.1 Pro
- Devstral Small 2 vs MiniCPM-V 4.7 1B
- DiffusionGemma 26B A4B IT vs Kimi K3.1 Pro
- DiffusionGemma 26B A4B IT vs MiniCPM-V 4.7 1B
- EXAONE 4.5 33B vs Kimi K3.1 Pro
- EXAONE 4.5 33B vs MiniCPM-V 4.7 1B
- Gemma 4 12B IT vs Kimi K3.1 Pro
- Gemma 4 12B IT vs MiniCPM-V 4.7 1B
- Gemma 4 26B A4B IT vs Kimi K3.1 Pro
- Gemma 4 26B A4B IT vs MiniCPM-V 4.7 1B
- Gemma 4 31B IT vs Kimi K3.1 Pro
- Gemma 4 31B IT vs MiniCPM-V 4.7 1B
- Gemma 4 E2B IT vs Kimi K3.1 Pro
- Gemma 4 E2B IT vs MiniCPM-V 4.7 1B
- Gemma 4 E4B IT vs Kimi K3.1 Pro
- Gemma 4 E4B IT vs MiniCPM-V 4.7 1B
- GLM-4.5-Air vs Kimi K3.1 Pro
- GLM-4.5-Air vs MiniCPM-V 4.7 1B
- GLM-4.7-Flash vs Kimi K3.1 Pro
- GLM-4.7-Flash vs MiniCPM-V 4.7 1B
- GLM-5.3-Flash vs Kimi K3.1 Pro
- GLM-5.3-Flash vs MiniCPM-V 4.7 1B
- GLM-5.3 vs Kimi K3.1 Pro
- GLM-5.3 vs MiniCPM-V 4.7 1B
- gpt-oss-120b vs Kimi K3.1 Pro
- gpt-oss-120b vs MiniCPM-V 4.7 1B
- gpt-oss-20b vs Kimi K3.1 Pro
- gpt-oss-20b vs MiniCPM-V 4.7 1B
- Granite 4.2 30B vs Kimi K3.1 Pro
- Granite 4.2 30B vs MiniCPM-V 4.7 1B
- Granite 4.2 3B vs Kimi K3.1 Pro
- Granite 4.2 3B vs MiniCPM-V 4.7 1B
- Granite 4.2 8B vs Kimi K3.1 Pro
- Granite 4.2 8B vs MiniCPM-V 4.7 1B
- Hy-Memory-30B-A3B vs Kimi K3.1 Pro
- Hy-Memory-30B-A3B vs MiniCPM-V 4.7 1B
- Hy3 vs Kimi K3.1 Pro
- Hy3 vs MiniCPM-V 4.7 1B
- Inkling-Small vs Kimi K3.1 Pro
- Inkling-Small vs MiniCPM-V 4.7 1B
- Inkling vs Kimi K3.1 Pro
- Inkling vs MiniCPM-V 4.7 1B
- InternVL3.5-GPT-OSS-20B-A4B-Preview vs Kimi K3.1 Pro
- InternVL3.5-GPT-OSS-20B-A4B-Preview vs MiniCPM-V 4.7 1B
- Kimi K3.1 Pro vs Kolibri-1
- Kimi K3.1 Pro vs Kronos
- Kimi K3.1 Pro vs Laguna M.1
- Kimi K3.1 Pro vs Laguna S 2.1
- Kimi K3.1 Pro vs Laguna XS 2.1
- Kimi K3.1 Pro vs LBS-27B
- Kimi K3.1 Pro vs LFM2.5-2.6B
- Kimi K3.1 Pro vs LFM3-1.7B
- Kimi K3.1 Pro vs LFM3-Audio-2B
- Kimi K3.1 Pro vs LFM3-Omni-2B
- Kimi K3.1 Pro vs LFM3-VL-2B
- Kimi K3.1 Pro vs Ling-3.0-tiny
- Kimi K3.1 Pro vs Ling-3.1-flash-1019
- Kimi K3.1 Pro vs LongCat-2.5
- Kimi K3.1 Pro vs MiMo-V2.6 Distill Qwen 9B
- Kimi K3.1 Pro vs MiMo-V2.6-Flash-RL
- Kimi K3.1 Pro vs MiniCPM-o 4.5
- Kimi K3.1 Pro vs MiniCPM-V 4.7 35B-A3B
- Kimi K3.1 Pro vs MiniCPM5-2B
- Kimi K3.1 Pro vs MiniMax-M2.5
- Kimi K3.1 Pro vs MiniMax-M2.7
- Kimi K3.1 Pro vs MiniMax-M3.1-Flash
- Kimi K3.1 Pro vs Mistral Large 4
- Kimi K3.1 Pro vs Muse Glimmer 30B
- Kimi K3.1 Pro vs Nanbeige4.2-3B
- Kimi K3.1 Pro vs Nanbeige4.3-33B
- Kimi K3.1 Pro vs NVIDIA Nemotron 3.5 Bolt E4B 4GB
- Kimi K3.1 Pro vs Nemotron 3.5 Lightning 30B A3B
- Kimi K3.1 Pro vs Nemotron 3 Nano 30B A3B
- Kimi K3.1 Pro vs Nemotron 3 Nano 4B
- Kimi K3.1 Pro vs Nemotron 3 Nano Omni 30B A3B Reasoning
- Kimi K3.1 Pro vs Nemotron 3 Super 120B A12B
- Kimi K3.1 Pro vs Nemotron 3 Ultra 550B A55B
- Kimi K3.1 Pro vs North Mini Code 1.0
- Kimi K3.1 Pro vs occamy-1.0
- Kimi K3.1 Pro vs Olmo 3 7B Think
- Kimi K3.1 Pro vs Ornith-1.5-122B
- Kimi K3.1 Pro vs Ornith-1.5-35B-A3B
- Kimi K3.1 Pro vs Ornith-1.5-397B
- Kimi K3.1 Pro vs Ornith-1.5-9B
- Kimi K3.1 Pro vs OTel-2.0-LLM-31B-IT
- Kimi K3.1 Pro vs Qwen-AgentWorld-35B-A3B
- Kimi K3.1 Pro vs Qwen3-30B-A3B-Instruct-2507
- Kimi K3.1 Pro vs Qwen3-4B-Instruct-2507
- Kimi K3.1 Pro vs Qwen3.5-0.8B
- Kimi K3.1 Pro vs Qwen3.5-122B-A10B
- Kimi K3.1 Pro vs Qwen3.5-2B
- Kimi K3.1 Pro vs Qwen3.5-397B-A17B
- Kimi K3.1 Pro vs Qwen3.5-4B
- Kimi K3.1 Pro vs Qwen3.5-9B
- Kimi K3.1 Pro vs Qwen3.6-27B
- Kimi K3.1 Pro vs Qwen3.6-35B-A3B
- Kimi K3.1 Pro vs Qwen3.8-27B
- Kimi K3.1 Pro vs Qwen3.8-Flash-Next
- Kimi K3.1 Pro vs Qwen3-Coder-30B-A3B-Instruct
- Kimi K3.1 Pro vs Qwen3-Coder-Next
- Kimi K3.1 Pro vs Qwen3-Omni-30B-A3B-Instruct
- Kimi K3.1 Pro vs Qwen3-VL-2B-Instruct
- Kimi K3.1 Pro vs Qwen3-VL-30B-A3B-Instruct
- Kimi K3.1 Pro vs Qwen3-VL-32B-Instruct
- Kimi K3.1 Pro vs Qwen3-VL-4B-Instruct
- Kimi K3.1 Pro vs Qwen3-VL-8B-Instruct
- 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
- Kimi K3 vs MiniCPM-V 4.7 1B
- Kolibri-1 vs MiniCPM-V 4.7 1B
- Kronos vs MiniCPM-V 4.7 1B
- Laguna M.1 vs MiniCPM-V 4.7 1B
- Laguna S 2.1 vs MiniCPM-V 4.7 1B
- Laguna XS 2.1 vs MiniCPM-V 4.7 1B
- LBS-27B vs MiniCPM-V 4.7 1B
- LFM2.5-2.6B vs MiniCPM-V 4.7 1B
- LFM3-1.7B vs MiniCPM-V 4.7 1B
- LFM3-Audio-2B vs MiniCPM-V 4.7 1B
- LFM3-Omni-2B vs MiniCPM-V 4.7 1B
- LFM3-VL-2B vs MiniCPM-V 4.7 1B
- Ling-3.0-tiny vs MiniCPM-V 4.7 1B
- Ling-3.1-flash-1019 vs MiniCPM-V 4.7 1B
- LongCat-2.5 vs MiniCPM-V 4.7 1B
- MiMo-V2.6 Distill Qwen 9B vs MiniCPM-V 4.7 1B
- MiMo-V2.6-Flash-RL vs MiniCPM-V 4.7 1B
- MiniCPM-o 4.5 vs MiniCPM-V 4.7 1B
- MiniCPM-V 4.7 1B vs MiniCPM-V 4.7 35B-A3B
- MiniCPM-V 4.7 1B vs MiniCPM5-2B
- MiniCPM-V 4.7 1B vs MiniMax-M2.5
- MiniCPM-V 4.7 1B vs MiniMax-M2.7
- MiniCPM-V 4.7 1B vs MiniMax-M3.1-Flash
- MiniCPM-V 4.7 1B vs Mistral Large 4
- MiniCPM-V 4.7 1B vs Muse Glimmer 30B
- MiniCPM-V 4.7 1B vs Nanbeige4.2-3B
- MiniCPM-V 4.7 1B vs Nanbeige4.3-33B
- MiniCPM-V 4.7 1B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB
- MiniCPM-V 4.7 1B vs Nemotron 3.5 Lightning 30B A3B
- MiniCPM-V 4.7 1B vs Nemotron 3 Nano 30B A3B
- MiniCPM-V 4.7 1B vs Nemotron 3 Nano 4B
- MiniCPM-V 4.7 1B vs Nemotron 3 Nano Omni 30B A3B Reasoning
- MiniCPM-V 4.7 1B vs Nemotron 3 Super 120B A12B
- MiniCPM-V 4.7 1B vs Nemotron 3 Ultra 550B A55B
- MiniCPM-V 4.7 1B vs North Mini Code 1.0
- MiniCPM-V 4.7 1B vs occamy-1.0
- MiniCPM-V 4.7 1B vs Olmo 3 7B Think
- MiniCPM-V 4.7 1B vs Ornith-1.5-122B
- MiniCPM-V 4.7 1B vs Ornith-1.5-35B-A3B
- MiniCPM-V 4.7 1B vs Ornith-1.5-397B
- MiniCPM-V 4.7 1B vs Ornith-1.5-9B
- MiniCPM-V 4.7 1B vs OTel-2.0-LLM-31B-IT
- MiniCPM-V 4.7 1B vs Qwen-AgentWorld-35B-A3B
- MiniCPM-V 4.7 1B vs Qwen3-30B-A3B-Instruct-2507
- MiniCPM-V 4.7 1B vs Qwen3-4B-Instruct-2507
- MiniCPM-V 4.7 1B vs Qwen3.5-0.8B
- MiniCPM-V 4.7 1B vs Qwen3.5-122B-A10B
- MiniCPM-V 4.7 1B vs Qwen3.5-2B
- MiniCPM-V 4.7 1B vs Qwen3.5-397B-A17B
- MiniCPM-V 4.7 1B vs Qwen3.5-4B
- MiniCPM-V 4.7 1B vs Qwen3.5-9B
- MiniCPM-V 4.7 1B vs Qwen3.6-27B
- MiniCPM-V 4.7 1B vs Qwen3.6-35B-A3B
- MiniCPM-V 4.7 1B vs Qwen3.8-27B
- MiniCPM-V 4.7 1B vs Qwen3.8-Flash-Next
- MiniCPM-V 4.7 1B vs Qwen3-Coder-30B-A3B-Instruct
- MiniCPM-V 4.7 1B vs Qwen3-Coder-Next
- MiniCPM-V 4.7 1B vs Qwen3-Omni-30B-A3B-Instruct
- MiniCPM-V 4.7 1B vs Qwen3-VL-2B-Instruct
- MiniCPM-V 4.7 1B vs Qwen3-VL-30B-A3B-Instruct
- MiniCPM-V 4.7 1B vs Qwen3-VL-32B-Instruct
- MiniCPM-V 4.7 1B vs Qwen3-VL-4B-Instruct
- MiniCPM-V 4.7 1B vs Qwen3-VL-8B-Instruct
- MiniCPM-V 4.7 1B vs Qwopus3.8-27B-Flash-V2
- MiniCPM-V 4.7 1B vs Recursive Flint
- MiniCPM-V 4.7 1B vs Ripple-65B Preview
- MiniCPM-V 4.7 1B vs SenseNova-Loop-9B-Preview
- MiniCPM-V 4.7 1B vs SmolLM3-3B
- MiniCPM-V 4.7 1B vs Spark-X2.6-4B
- MiniCPM-V 4.7 1B vs Step 3.7 Flash
- MiniCPM-V 4.7 1B vs Swift 1.5 Qwen3.8-27B
- MiniCPM-V 4.7 1B vs Swift 1.5 Qwen3.8-Flash-Next
- MiniCPM-V 4.7 1B vs ThinkingCap (Qwen3.8 27B)
- MiniCPM-V 4.7 1B vs Baidu Unlimited-OCR-2
- MiniCPM-V 4.7 1B vs WeVisOne-VL-2B
- MiniCPM-V 4.7 1B vs WeVisOne-VL-4B
- MiniCPM-V 4.7 1B vs ZAYA1-8B
Machine-readable
- This page as Markdown
/compare/kimi-k3-1-pro-vs-minicpm-v-4-7-1b.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/minicpm-v-4-7-1b.json - From a terminal
anchor compare kimi-k3-1-pro minicpm-v-4-7-1b(the CLI) - Over MCP
compare_tools {"a": "kimi-k3-1-pro", "b": "minicpm-v-4-7-1b"}at/mcp, no key