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ModelCap

Llama 3.2 1B Instruct

Arena #401Official publisher releaseGated access6.9d #353 → #348

Meta·#348 of 352 on the current board·cheaper than #339 Llama 3.2 3B Instruct

Llama 3.2 1B Instruct is a language model from Meta. It ranks #348 of 352 on ModelCap's current board, with an Index score of 4.6, measured on 2 public benchmarks. Its score range of 0.0–10.2 spans positions #335–#352. It is listed at $0.027 per million input tokens and $0.201 per million output tokens from one provider. It reads up to 60K tokens of context, and its weights are downloadable after an access request.

Figures as of 6 Nov 2026, 20:32 UTC · download the public dataset · methodology

ModelCap Index · Current board
4.6#348
Measured on 2 public benchmarks · range 0.0–10.2
Evidence as of 28 Oct 2026, 00:00 UTC
Market Gravity
18.2Increased by 0.1
Secondary market signal
Input
$0.027
per 1M tokens
Output
$0.201
per 1M tokens
Context
60K
tokens
Providers
1
endpoint

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Cloudflare$0.027$0.20160K—100.0%

Reported evaluation leads (1)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.

Dataset / taskMetricValueRevisionProvenance
Idavidrein/gpqa
diamond
—18.6869
Unpinned
not published
Reported
Quarantined

ModelCap Index · Current board

Methodology
4.6
Measured on 2 public benchmarks
Current board
#348 of 352
Score range
0.0–10.2
Rank range
#335–#352
Evidence as of
28 Oct 2026, 00:00 UTC
Benchmarks used
Arena Coding, Arena Overall
Technical details
Public rank basis
Measured (measured)
Evidence label
Measured · 2 public benchmark observations across 2 boards
Index support
54.7% · moderate
Identity binding
Exact catalogue product · meta-llama/meta-llama/llama-3.2-1b-instruct · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata meta-llama/Llama-3.2-1B-Instruct@9213176726f574b556790deb65791e0c5aa438b6 (not the evaluation revision)
Index observations used
2
Qualified Index evidence point
4.6
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
4.6
Evidence status
confirmed · 75% mass
General preference
4.5
Coding
5.3
Agents & tools
—
Reasoning
—
Evidence breadth
92%
Evidence coverage
55%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
3.3
Liquidity (providers × uptime)
34.4
Open reach (HF downloads)
—
Surface (context / tools / modalities)
19.5
Freshness
5.3
  • · OpenRouter popularity #279
  • · 1 live provider
  • · Catalogue: context 60000
  • · First seen 2024-09-25

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

BES evidence selected · measured input only

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Deployment readiness

Metadata index
69.5
partial · 89% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
68.3
Deployability
68.0
Evaluation provenance
49.7

Not yet published: the base model it derives from, a link to the licence terms, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
18.2
OpenRouter weekly popularity
#279 of 339

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

Status
Ranked
Source
LMArena
Official rank
#401 of 419
Rating
1111.1
95% confidence interval
1103–1119
Votes
8K
Source published at
28 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
3.3

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
34.4

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
50.0

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
5.3

Time since first public availability, on a six-month half-life.

Specification

Model ID
meta-llama/llama-3.2-1b-instruct
Context window
60K tokens
Declared output cap
54K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text
Outputs
Text
Tokenizer
Llama3
Cached input tokens
Not offered
First seen on OpenRouter
25 Sept 2024
Knowledge cutoff
2023-12-31

Capabilities

  • Not supported: Reasoning
  • Not supported: Tool use
  • Not supported: Structured output
  • Not supported: Response format
  • Not supported: Moderated

Weights & access

Gated access. The weights are hosted behind an access request or acceptance step. Review the publisher's access requirements and license before use or redistribution.

Access
Gated access
Licence
llama3.2
Pinned revision
9213176726f5
Parameters
1.2B
Architecture
LlamaForCausalLM
Model type
llama
Hugging Face downloads (30d)
1.5M
Downloads (all time)
109.6M
Likes
2K
Repository updated
24 Oct 2024, 15:07 UTC

Compare Llama 3.2 1B Instruct with

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Benchmark leaderboards featuring Llama 3.2 1B Instruct

All leaderboards
Public benchmark boards on which Llama 3.2 1B Instruct has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)11111103–1119#401 of 419Not reported28 Oct 2026
Arena coding leaderboardArena (LMArena)11491133–1165#393 of 414Default28 Oct 2026
BFCL V4 function-calling leaderboardUC Berkeley (Gorilla)10.8#81 of 83Function calling12 Apr 2026

Alternatives to Llama 3.2 1B Instruct, by the numbers

Ranked neighbours

Models within 3 places of #348 on the ModelCap Index.

Cheaper at a similar or higher Index

Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).

Other ranked Meta models

The same publisher's other current models with a public Index position.

Llama 3.2 1B Instruct: common questions

How does Llama 3.2 1B Instruct rank among AI models?

Llama 3.2 1B Instruct holds ModelCap Index position #348 of 352 ranked language models as of 6 November 2026, with an Index score of 4.6 (interval 0.0–10.2); evidence: measured. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does Llama 3.2 1B Instruct cost per 1M tokens?

Llama 3.2 1B Instruct is listed at $0.027 per 1M input tokens and $0.201 per 1M output tokens as of 6 November 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.154 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of Llama 3.2 1B Instruct?

Llama 3.2 1B Instruct has a published context window of 60K tokens (60,000). The snapshot lists a 54,000 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is Llama 3.2 1B Instruct open-weight?

Gated access (llama3.2). The weights are hosted behind an access request or acceptance step. Review the publisher's access requirements and license before use or redistribution. The repository is meta-llama/Llama-3.2-1B-Instruct on Hugging Face.

Which API providers serve Llama 3.2 1B Instruct?

One provider serves Llama 3.2 1B Instruct through OpenRouter as of 6 November 2026: Cloudflare. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has Llama 3.2 1B Instruct been evaluated on?

Llama 3.2 1B Instruct has published results on 3 public boards tracked by ModelCap as of 6 November 2026: Arena text 1111 (#401 of 419), Arena coding 1149 (#393 of 414) and BFCL V4 10.8 (#81 of 83). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

How does Llama 3.2 1B Instruct compare with Llama 3.2 3B Instruct?

Llama 3.2 1B Instruct ranks #348 (Index 4.6) and Llama 3.2 3B Instruct ranks #339 (Index 8.1) on the ModelCap Index as of 6 November 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.

When was Llama 3.2 1B Instruct released?

Llama 3.2 1B Instruct first appeared in the catalogue on 25 Sept 2024, with a published knowledge cutoff of 2023-12-31. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.