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Data

Data as of October 7, 2026 · How the score is built

CurrentOpen WeightReasoning

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

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 changes

Category 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 scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticWeight 22%1 benchmarkVerified
Score pending
CodingWeight 20%2 benchmarksVerified
Score pending
ReasoningWeight 17%1 benchmarkVerified
Score pending
MultimodalWeight 12%0 benchmarksNot measured
Not measured
KnowledgeRank #174 of 174Percentile 0thWeight 12%4 benchmarksVerified
7.8
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingRank #123 of 125Percentile 2ndWeight 5%2 benchmarksVerified
9.7
MathRank Not rankedWeight 5%4 benchmarksVerified
5.4

14 of 665 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How 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.

  1. Agentic1/1 verified
  2. Coding2/2 verified
  3. Reasoning1/1 verified
  4. MultimodalNot measured
  5. Knowledge4/4 verified
  6. MultilingualNot measured
  7. Inst. Following2/2 verified
  8. Math4/4 verified
Verified sourceProvisionalNot measured

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

  1. AgenticNot ranked
  2. CodingNot ranked
  3. ReasoningNot ranked
  4. MultimodalNot ranked
  5. Knowledge#174/174
  6. MultilingualNot ranked
  7. Inst. Following#123/125
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

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
Coding benchmark values, best verified comparison, weight, and source status
LiveCodeBench ProScore22.7%Versus best verified row

Best verified: Sakana Fugu-Ultra · 90.8%

Gap68.1 behindWeightDisplay only
LiveCodeBench v6Score33.5%Versus best verified row

Best verified: Sakana Fugu-Ultra · 93.2%

Gap59.7 behindWeightDisplay only
Agentic1 row
Agentic benchmark values, best verified comparison, weight, and source status
BFCL v4Berkeley Function Calling Leaderboard v4Score25.1%Versus best verified row

Best verified: BTL-3 · 88.5%

Gap63.4 behindWeight3% ref. weight
Reasoning1 row
Reasoning benchmark values, best verified comparison, weight, and source status
BBHBIG-Bench HardScore71.9%Versus best verified row

Best verified: Soofi S 30B-A3B · 78.8%

Gap6.9 behindWeightDisplay only
Knowledge4 rows
Knowledge benchmark values, best verified comparison, weight, and source status
MMLU-ProMassive Multitask Language Understanding ProfessionalScore48.9%Versus best verified row

Best verified: Qwen3.7 Max · 89.6%

Gap40.7 behindWeight6% ref. weight
SuperGPQASuperGPQA: Scaling LLM Evaluation Across 285 Graduate DisciplinesScore23.1%Versus best verified row

Best verified: Qwen 3.6 Max (preview) · 73.9%

Gap50.8 behindWeight2% ref. weight
MMLU-ReduxScore70.1%Versus best verified row

Best verified: Qwen3.7 Max · 95%

Gap24.9 behindWeightDisplay only
GPQA-DGPQA DiamondScore26.3%Versus best verified row

Best verified: GPT-6 Astra · 96.0%

Gap69.7 behindWeightDisplay only
Inst. Following2 rows
Inst. Following benchmark values, best verified comparison, weight, and source status
IFBenchInstruction Following BenchmarkScore46.7%Versus best verified row

Best verified: MAI-Thinking-1 · 85%

Gap38.3 behindWeightWeighted 70%
IFEvalInstruction-Following EvalScore80.4%Versus best verified row

Best verified: Qwen3.5-27B · 95%

Gap14.6 behindWeightDisplay only
Math4 rows
Math benchmark values, best verified comparison, weight, and source status
AIME26AIME 2026Score40.4%Versus best verified row

Best verified: GLM-5.2 · 99.2%

Gap58.8 behindWeightWeighted 25%
HMMT Feb 2026Harvard-MIT Mathematics Tournament February 2026Score25.8%Versus best verified row

Best verified: Qwen3.7 Max · 97.1%

Gap71.3 behindWeightWeighted 25%
AIME 2025American Invitational Mathematics Examination 2025Score40.4%Versus best verified row

Best verified: MAI-Thinking-1 · 97%

Gap56.6 behindWeightDisplay only
MATH-500MATH-500 Problem SetScore91.6%Versus best verified row

Best verified: Ternary Bonsai 2 27B · 98.8%

Gap7.2 behindWeightDisplay only

Bars run 0–100; the dark tick marks the best source-verified value

All 14 rows

Lineage

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.

  1. May 25, 2026 · you are here

    MiniCPM5-1B

    Score 5.1 · Price not listed

Radar

MiniCPM5-1B release history

Full 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 parameters

Questions

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.

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Compare MiniCPM5-1B with every tracked model886 comparisons