# MiniCPM-V 4.7 1B vs OTel-2.0-LLM-31B-IT

> MiniCPM-V 4.7 1B scores 61 (C) to OTel-2.0-LLM-31B-IT's 56.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-otel-2-0-llm-31b-it
- Markdown: https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-otel-2-0-llm-31b-it.md (~9,900 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-10

MiniCPM-V 4.7 1B scores 61 (C) on agent readiness against OTel-2.0-LLM-31B-IT's 56.8 (C), and leads in 2 of 4 scored categories. OTel-2.0-LLM-31B-IT leads on documentation and upkeep. Both do open-weight models you run yourself.

- MiniCPM-V 4.7 1B: grade C, 61/100, rank #76 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/minicpm-v-4-7-1b.md · JSON https://www.anchorterminal.com/api/v1/tools/minicpm-v-4-7-1b.json
- OTel-2.0-LLM-31B-IT: grade C, 56.8/100, rank #111 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/otel-2-0-llm-31b-it.md · JSON https://www.anchorterminal.com/api/v1/tools/otel-2-0-llm-31b-it.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### MiniCPM-V 4.7 1B (C)

Good 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 50
- Agent interface, 70 against 60

Watch for: No limitations section, safety results, agent-use guidance or security contact

### OTel-2.0-LLM-31B-IT (C)

Good for: Telecoms teams that want an open model for standards questions and RAG on their own hardware

Ahead on:
- Documentation and upkeep, 74 against 48

Watch for: BF16 only at 62.6 GB, with no GGUF or other quantised build from anyone we checked


## Why the edge

### Reach: MiniCPM-V 4.7 1B +45

- 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.
- OTel-2.0-LLM-31B-IT (50): Memory 10, the publisher's only build is the BF16 safetensors, 62.55 GB for the 15 shards the index names, and 62.55 GB × 1.2 = 75.1 GB, above 64 GB and inside the reference machine's GPU share. Runtimes 15, the architecture is Gemma4ForConditionalGeneration, which vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 run from the safetensors files, three at 5 each. Builds 0, the publisher ships the BF16 weights only. Terms 15, Apache 2.0 in the card's metadata, an OSI licence, with nothing added on the card. Download 10, gated is false on 10 November 2026, so the files download with no account or terms. Hosted 0, Hugging Face maps one inference provider, Featherless AI (live), short of the two the line needs. 10 + 15 + 0 + 15 + 10 + 0 = 50.

### Documentation and upkeep: OTel-2.0-LLM-31B-IT +26

- 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.
- OTel-2.0-LLM-31B-IT (74): Model card 14, Intended use, a long limitations section, the architecture and training method, the parameters (31B) and the language (English) are on the card. Training data 15, the card names the sources (3GPP, ETSI, ITU, GSMA, CAMARA, O-RAN and TM Forum material provided by GSMA), the overall sizes (15 billion raw tokens, over 1 trillion processed, about 440 billion used), the mix of example types and the processing tool, and lists what was left out. Last change 20, the last commit, on 1 November 2026, updated the card's links, resources, citation and contacts, nine days before this check. Responsiveness 20, Of the 3 discussions that aren't pull requests (7 August to 28 October 2026), 2 have a reply from the repository's owner, which is most. Version policy 0, the weights were replaced in place: uploads on 27 July, 3 August and 1 September 2026 under one name, with a standing notice on the card that they may change and that users should pin a revision, and no dated note of what changed. File health 5, the card describes 15 shards of about 62.6 GB while the repository still holds an earlier 14-shard set beside them, 126.8 GB in all. 14 + 15 + 20 + 20 + 0 + 5 = 74.

### Agent interface: MiniCPM-V 4.7 1B +10

- 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.
- OTel-2.0-LLM-31B-IT (60): Chat template 20, chat_template.jinja in the repository, 19,300 characters, the publisher's own. Tool-calling format 10, only the template says how tools are declared and how calls come back. Trained tool calling 20, the template loops over tool_calls, so it renders several calls in one turn, and the card says the training mix included general-purpose agentic tool-calling examples, while none were specific to telecoms. Structured output 0, the card doesn't document JSON or JSON Schema output. Reasoning control 0, the card says the model wasn't trained to produce or consume Gemma's thought channel and answers directly, so there is no thinking to switch or budget. Context 10, 262,144 positions in the text config, the base's native context. 20 + 10 + 20 + 0 + 0 + 10 = 60.

## Score by category

| Category | Weight | MiniCPM-V 4.7 1B | OTel-2.0-LLM-31B-IT | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35%, pending | pending | pending | not scored in this run |
| Reach | 25% (25 this run) | 95 | 50 | MiniCPM-V 4.7 1B +45 |
| Risk | 20% (20 this run) | 55 | 55 | even |
| Agent interface | 10% (10 this run) | 70 | 60 | MiniCPM-V 4.7 1B +10 |
| Documentation and upkeep | 10% (10 this run) | 48 | 74 | OTel-2.0-LLM-31B-IT +26 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61 · C** | **56.8 · C** | |

## Facts side by side

| Fact | MiniCPM-V 4.7 1B | OTel-2.0-LLM-31B-IT |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | OpenBMB | AT&T (Open Telco AI) |
| 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 | 2026-10-30 | 2026-11-01 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |

## Verdicts

**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.

**OTel-2.0-LLM-31B-IT.** A real telecoms post-training of Gemma 4 31B IT with an unusually candid card on what was and wasn't trained. It fits a 128 GB machine in BF16 only, with no quantised build, sits in a personal account, and its weights have been replaced in place. Tool-call format, structured output and safety results aren't documented.

## Before you call either

### MiniCPM-V 4.7 1B

1. Start it with `llama-server -hf openbmb/MiniCPM-V-4.7-1B-gguf:Q4_K_M --jinja`, or `ollama run openbmb/minicpm-v4.7:1b`
2. For image input in llama.cpp add `mmproj-model-f16.gguf`, or the smaller 4x projector
3. The GGUF files at the repository root have thinking off. Use the files in `thinking/` when you want the trace
4. Use temperature 0.7, top_p 0.95 and top_k 100 in instruct mode, as the card recommends
5. Check tool calls in your runtime first, since the card names no parser
6. Validate JSON output yourself, since structured output isn't documented

### OTel-2.0-LLM-31B-IT

1. Download the 15 shards the index names, not the whole repository, which is twice the size
2. Pin a revision. The card says the weights may change under the same name
3. Serve it with vLLM 0.19.0 or later and the repository's own chat template, not Gemma 4's
4. Send no thinking flags. It answers directly and wasn't trained on Gemma's thought channel
5. Use it as the generation stage of a RAG pipeline over telecom standards, with source attribution and human review
6. Don't use it to run network tools unattended. The card says that hasn't been evaluated

## Questions

### Which is better for AI agents, MiniCPM-V 4.7 1B or OTel-2.0-LLM-31B-IT?

MiniCPM-V 4.7 1B scores 61 (C) on agent readiness against OTel-2.0-LLM-31B-IT's 56.8 (C), and leads in 2 of 4 scored categories. OTel-2.0-LLM-31B-IT leads on documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-otel-2-0-llm-31b-it.json, and with the fewest tokens: https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-otel-2-0-llm-31b-it.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "minicpm-v-4-7-1b", "b": "otel-2-0-llm-31b-it"}`. From a terminal: `anchor compare minicpm-v-4-7-1b otel-2-0-llm-31b-it`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/minicpm-v-4-7-1b.json and https://www.anchorterminal.com/api/v1/tools/otel-2-0-llm-31b-it.json

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