OpenBMB · Model release
Data as of October 7, 2026 · How the score is built
Released May 25, 2026131K context
MiniCPM5-1B
Decision readingMiniCPM5-1B scores 5.1 out of 100 and ranks #216 of 216. This profile shows 14 source-displayable benchmark rows; its strongest eligible category is Instruction Following at #123. No comparable first-party API price is published in the catalog.
Released May 25, 2026 — see all recent releases
MiniCPM5-1B will be repriced, updated or retired. Get each notice with its source and date. Follow model changes
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
5.1/100
field median 52.1#216 of 216 ranked models
Public
#216of 216
Verified —
Price
Not listed
input median $0.95No comparable first-party hosted token rate
Speed
Not measured
field median 97 tok/sTime to first token not measured
Context
131Ktokens
field median 256,000Reported for this model; direct source link not stored
Strongest published evidence
Instruction Following ranks #123. A well-rounded choice across a range of tasks.
Validate before choosing
14 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.
Source-linked · 14 displayable benchmark rows
Follow model changesCategory score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticWeight 22%1 benchmarkVerified | Score pending | 1 benchmark | Verified | |||
| CodingWeight 20%2 benchmarksVerified | Score pending | 2 benchmarks | Verified | |||
| ReasoningWeight 17%1 benchmarkVerified | Score pending | 1 benchmark | Verified | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeRank #174 of 174Percentile 0thWeight 12%4 benchmarksVerified | 7.8 | 4 benchmarks | Verified | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingRank #123 of 125Percentile 2ndWeight 5%2 benchmarksVerified | 9.7 | 2 benchmarks | Verified | |||
| MathRank Not rankedWeight 5%4 benchmarksVerified | 5.4 | 4 benchmarks | Verified |
14 of 665 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic1/1 verified
- Coding2/2 verified
- Reasoning1/1 verified
- MultimodalNot measured
- Knowledge4/4 verified
- MultilingualNot measured
- Inst. Following2/2 verified
- Math4/4 verified
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
MiniCPM5-1B category percentile values
- AgenticNot eligible
- CodingNot eligible
- ReasoningNot eligible
- MultimodalNot eligible
- Knowledge0th percentile
- MultilingualNot eligible
- Instruction following2nd percentile
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- AgenticNot ranked
- CodingNot ranked
- ReasoningNot ranked
- MultimodalNot ranked
- Knowledge#174/174
- MultilingualNot ranked
- Inst. Following#123/125
- MathNot ranked
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| LiveCodeBench Pro | Score22.7% | Versus best verified row Best verified: Sakana Fugu-Ultra · 90.8% | Gap68.1 behind | WeightDisplay only | Provider exact |
| LiveCodeBench v6 | Score33.5% | Versus best verified row Best verified: Sakana Fugu-Ultra · 93.2% | Gap59.7 behind | WeightDisplay only | Provider exact |
Agentic1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| BFCL v4Berkeley Function Calling Leaderboard v4 | Score25.1% | Versus best verified row Best verified: BTL-3 · 88.5% | Gap63.4 behind | Weight3% ref. weight | Provider exact |
Reasoning1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| BBHBIG-Bench Hard | Score71.9% | Versus best verified row Best verified: Soofi S 30B-A3B · 78.8% | Gap6.9 behind | WeightDisplay only | Provider exact |
Knowledge4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMLU-ProMassive Multitask Language Understanding Professional | Score48.9% | Versus best verified row Best verified: Qwen3.7 Max · 89.6% | Gap40.7 behind | Weight6% ref. weight | Provider exact |
| SuperGPQASuperGPQA: Scaling LLM Evaluation Across 285 Graduate Disciplines | Score23.1% | Versus best verified row Best verified: Qwen 3.6 Max (preview) · 73.9% | Gap50.8 behind | Weight2% ref. weight | Provider exact |
| MMLU-Redux | Score70.1% | Versus best verified row Best verified: Qwen3.7 Max · 95% | Gap24.9 behind | WeightDisplay only | Provider exact |
| GPQA-DGPQA Diamond | Score26.3% | Versus best verified row Best verified: GPT-6 Astra · 96.0% | Gap69.7 behind | WeightDisplay only | Provider exact |
Inst. Following2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| IFBenchInstruction Following Benchmark | Score46.7% | Versus best verified row Best verified: MAI-Thinking-1 · 85% | Gap38.3 behind | WeightWeighted 70% | Provider exact |
| IFEvalInstruction-Following Eval | Score80.4% | Versus best verified row Best verified: Qwen3.5-27B · 95% | Gap14.6 behind | WeightDisplay only | Provider exact |
Math4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| AIME26AIME 2026 | Score40.4% | Versus best verified row Best verified: GLM-5.2 · 99.2% | Gap58.8 behind | WeightWeighted 25% | Provider exact |
| HMMT Feb 2026Harvard-MIT Mathematics Tournament February 2026 | Score25.8% | Versus best verified row Best verified: Qwen3.7 Max · 97.1% | Gap71.3 behind | WeightWeighted 25% | Provider exact |
| AIME 2025American Invitational Mathematics Examination 2025 | Score40.4% | Versus best verified row Best verified: MAI-Thinking-1 · 97% | Gap56.6 behind | WeightDisplay only | Provider exact |
| MATH-500MATH-500 Problem Set | Score91.6% | Versus best verified row Best verified: Ternary Bonsai 2 27B · 98.8% | Gap7.2 behind | WeightDisplay only | Provider exact |
Bars run 0–100; the dark tick marks the best source-verified value
All 14 rowsLineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
MiniCPM5-1B release history
Radar confirmed these at the source. Use MiniCPM5-1B in your work? Explore Radar to follow supported changes and choose your alerts.
Radar
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not published
- Context window
- 131K
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- Not sourced yet
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing record
- Self-host
- Open weights available; hardware estimate not sourced
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
MiniCPM5-1B ranks #216 of 216 on the public leaderboard with a score of 5.12/100. It does not yet have enough sourced coverage for a verified position.
MiniCPM5-1B is a open weight model with a 131K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Tracked from OpenBMB's MiniCPM5-1B Hugging Face, GitHub, and ModelScope release pages. The official model card describes MiniCPM5-1B as an Apache-2.0 dense 1.08B LlamaForCausalLM checkpoint with BF16 safetensors, a 131,072-token context window, bilingual English/Chinese support, local/on-device deployment focus, tool-calling support, and hybrid Think / No Think chat modes via enable_thinking. BenchLM maps exact benchmark rows from OpenBMB's published MiniCPM5-1B evaluation table.
MiniCPM5-1B sits in the MiniCPM5 family with MiniCPM5-2B. 14 of 665 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Instruction Following at #123, while its lowest eligible position is Knowledge at #174. a well-rounded choice across a range of tasks.
Last updated October 7, 2026. Runtime fields remain blank until a sourced snapshot exists.
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.
Estimate VRAM from known parametersQuestions
How does MiniCPM5-1B perform overall in AI benchmarks?
MiniCPM5-1B ranks #216 out of 216 models on the public BenchAlign leaderboard, with a score of 5.12/100. Its evidence status is Estimated, and this profile shows 14 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is MiniCPM5-1B good for knowledge and understanding?
MiniCPM5-1B ranks #174 out of 174 eligible models for knowledge and understanding, with a public category score of 7.8/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is MiniCPM5-1B good for coding and programming?
MiniCPM5-1B has source-displayable benchmark coverage for coding and programming, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is MiniCPM5-1B good for mathematics?
MiniCPM5-1B has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is MiniCPM5-1B good for reasoning and logic?
MiniCPM5-1B has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is MiniCPM5-1B good for agentic tool use and computer tasks?
MiniCPM5-1B has source-displayable benchmark coverage for agentic tool use and computer tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is MiniCPM5-1B good for instruction following?
MiniCPM5-1B ranks #123 out of 125 eligible models for instruction following, with a public category score of 9.7/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is MiniCPM5-1B open source?
MiniCPM5-1B is an open-weight model from OpenBMB. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Which sibling models are related to MiniCPM5-1B?
MiniCPM5-1B belongs to the MiniCPM5 family. Related tracked variants include MiniCPM5-2B. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does MiniCPM5-1B have full benchmark coverage on BenchLM?
No. MiniCPM5-1B currently has 15 source-displayable rows across 665 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of MiniCPM5-1B?
MiniCPM5-1B has a reported context window of 131K in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.