Head to head · Open-weight models you run yourself · October 2026 research run
Apodex-1.1-mini vs MiniCPM-V 4.7 1B
Apodex-1.1-mini and MiniCPM-V 4.7 1B score within a point of each other on agent readiness, 61 (C) and 61 (C). MiniCPM-V 4.7 1B leads on reach 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
Best for Long-running agent tasks with tools on a 32 GB GPU or Mac, or through Apodex's API, under a plain licence
Ahead on
- Risk, 65 against 55
- Agent interface, 85 against 70
Watch for
No safety results, and agent guidance only from the harness
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 85
- Documentation and upkeep, 48 against 38
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.
Agent interface Apodex-1.1-mini +15
Apodex-1.1-mini 85
Chat template 20, a Jinja file in the repository. Tool-calling format 25, the card says how tools go in and come back and names the parser for SGLang and vLLM, with a full example. Trained tool calling 20, trained for native function calling with parallel calls. Structured output 0. Reasoning control 10, the template turns thinking off per request and the card says the reasoning comes back in reasoning_content. Context 10, 262,144 tokens.
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.
Reach MiniCPM-V 4.7 1B +10
Apodex-1.1-mini 85
Memory 20, Apodex's Q4_K_M GGUF with its vision projector is 22.6 GB and needs about 27.1 GB with the fifth added, so 32 GB, as do its NVFP4 and GPTQ-Int4 builds. Runtimes 20, the Qwen3.5 MoE architecture runs in released vLLM, SGLang, Transformers and llama.cpp, while Ollama's and LM Studio's entries are the base's, not this model's. Builds 15, Apodex publishes FP8, NVFP4, GPTQ-Int4 and GGUF. Terms 15, Apache 2.0 with nothing added. Download 10, nothing is gated. Hosted 5, Apodex's own API serves it.
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 Apodex-1.1-mini +10
Apodex-1.1-mini 65
File safety 25, safetensors and GGUF only and nothing from the repositories runs. Provenance 15, the files are in the apodex organisation its site links to, with a SHA-256 for every weight file and a SHA256SUMS file for the GGUF. Safety evaluation 0, none published. Agent guidance 5, the recommended harness documents approval gates and a sandbox boundary, but nothing on prompt injection or refusals for the model. Licence risk 15, Apache 2.0 from Qwen3.5-35B-A3B through to this model with no conditions added. Security programme 5, the harness has a disclosure policy with a private address, with no route shown for the weights.
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.
Documentation and upkeep MiniCPM-V 4.7 1B +10
Apodex-1.1-mini 38
Model card 8, it covers intended use, context and languages but not the architecture, parameters, limitations or a knowledge cut-off. Training data 5, a general description with no cut-off. Last change 15, the GGUF build went up on 10 September 2026, 54 days before 3 November. Responsiveness 0, Apodex answered none of the four discussions, unchanged on 3 November 2026. Version policy 5, 1.0-mini stays in its own repository without a note. File health 5, the files agree, but the card's agent example is broken and reports wait without a reply.
MiniCPM-V 4.7 1B 48
Model card 8, Intended use (image, multi-image and video understanding on device), architecture (early visual-token compression inside the vision encoder) and parameters (1B) are there. Training data 0, no description of the training data on the card. Last change 20, the last commit, on 30 October 2026, updated the card and removed an unused asset folder, eleven days before this check. Responsiveness 0, the repository has no discussions that aren't pull requests (two pull requests in all), so nobody has asked anything yet and the line reads as none answered, as settled in calibration. Version policy 10, MiniCPM-V 4.5 and 4.6 stay in their own repositories and the GitHub README dates each release. File health 10, Config, template and card agree on the architecture and the thinking switch, and no report waits without a reply, since there are no discussions. 8 + 0 + 20 + 0 + 10 + 10 = 48.
Score by category
| Category | Weight this run | Apodex-1.1-mini | MiniCPM-V 4.7 1B | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 85 | 95 | MiniCPM-V 4.7 1B +10 |
| Risk | 20%20 | 65 | 55 | Apodex-1.1-mini +10 |
| Agent interface | 10%10 | 85 | 70 | Apodex-1.1-mini +15 |
| Documentation and upkeep | 10%10 | 38 | 48 | MiniCPM-V 4.7 1B +10 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 61/100 | C 61/100 |
Facts side by side
| Fact | Apodex-1.1-mini | MiniCPM-V 4.7 1B |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Apodex AI | OpenBMB |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-08-25 | 2026-10-30 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 3.3/5 (4) | none |
Verdicts
Apodex-1.1-mini
An agent cousin fine-tuned from Qwen3.5-35B-A3B for long tasks with files, code and tools, with parallel tool calling and about 3B active parameters. It needs 32 GB for Apodex's GGUF, NVFP4 or GPTQ-Int4 builds or about 86 GB in BF16, and Apodex's API serves it too. The main risks are no safety results and no replies from the publisher.
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
Apodex-1.1-mini
- Serve it with
vllm serve apodex/Apodex-1.1-mini --enable-auto-tool-choice --tool-call-parser qwen3_coder --reasoning-parser qwen3, or the same parsers in SGLang, so tool calls and reasoning come back parsed - For llama.cpp,
llama-server -hf apodex/Apodex-1.1-mini-GGUF:Q4_K_M --jinja --reasoning-format deepseek, and the card passes the repository's chat_template.jinja with --chat-template-file - Pass tools through the API's tools parameter rather than in the system prompt, as the card asks
- The card recommends temperature 1.0, top_p 0.95, repetition_penalty 1.05 and max_tokens up to 32,768
- Send your own system prompt, or set identity_mode, since the template otherwise adds an Apodex identity block
- The template keeps all earlier reasoning in the context unless
preserve_thinkingis false, which grows long agent sessions - Thinking is on by default, send
chat_template_kwargswithenable_thinkingfalse for short tasks, a switch the card doesn't mention - The card's Python example has a broken line where it runs the tool (available_toolsname), so fix it to
available_tools[name](**args)before running - Validate JSON output yourself, since structured output isn't documented
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, Apodex-1.1-mini or MiniCPM-V 4.7 1B?
Apodex-1.1-mini and MiniCPM-V 4.7 1B score within a point of each other on agent readiness, 61 (C) and 61 (C). MiniCPM-V 4.7 1B leads on reach and documentation and upkeep.
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- 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/apodex-1-1-mini-vs-minicpm-v-4-7-1b.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/apodex-1-1-mini.json·/api/v1/tools/minicpm-v-4-7-1b.json - From a terminal
anchor compare apodex-1-1-mini minicpm-v-4-7-1b(the CLI) - Over MCP
compare_tools {"a": "apodex-1-1-mini", "b": "minicpm-v-4-7-1b"}at/mcp, no key