Llama 3.2 1B Instruct

MetaKey llama-3.2-1b-instruct

No public Tokscale usage yet

No public Tokscale submission includes Llama 3.2 1B Instruct yet, so this page has no active users, tokens or agent shares. The benchmark results, list prices and specs below come from public sources. See models with usage

Benchmarks

The best result for Llama 3.2 1B Instruct in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark.

All benchmarks
  • GPQA DiamondReasoning · Epoch AI
    23.9%
    Rank #157 of 160 matched modelsNo conditions reportedRun date Aug 30, 2026Source: epoch.ai (opens in a new tab)

    Near its ceiling: the top score is 96.5%, and Epoch AI estimates the reachable maximum at 97%. Differences between top models are small.

Not evaluated: Epoch Capabilities Index, Humanity's Last Exam, FrontierMath Tiers 1–3 (v2), SimpleQA Verified, Terminal-Bench 4.1, CursorBench, DeepSWE, FrontierSWE, Agent Arena, WebDev Arena. A missing result is not a score of zero.

Pricing

List prices from models.dev in US dollars per 1M tokens, retrieved Nov 12, 2026. OpenRouter is the reference price for the estimates below. It is the first provider listed; models.dev lists no price from the lab's own API.

Price at real agent usageEstimate at list prices

What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.

At the community mix
$0.03
Est. per 1M tokens
96% cache reads
3:1 input/output blend
$0.07
Per 1M tokens at list prices
No cache

Cache reads were 96% of all tokens in public Tokscale submissions in the last 30 days. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.

Assumptions

  • OpenRouter list prices per 1M tokens: input $0.03, output $0.20.
  • The community mix is the tokens of every identified model in the last 30 days.
  • This is an estimate at list prices, not what anyone paid.
  • Reasoning tokens are priced as output.
  • Long-context tiers, batch pricing and discounts are not applied.
  • Token mixes come from public Tokscale submissions. Hidden accounts are excluded.
  • No cache-read price is listed, so cache reads are priced as input.
  • No cache-write price is listed, so cache writes are priced as input.

List prices by provider

  • OpenRouterReferencemeta-llama/llama-3.2-1b-instruct
    $0.03 input per 1M tokens$0.20 output per 1M tokensCache read not listedCache write not listed60K tokens of context

Specs

From models.dev (MIT), retrieved Nov 12, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.

Context window
60K tokens
Max output
54K tokens
Input
Text
Output
Text
Knowledge cutoff
Dec 2023
Release date
Sep 25, 2024
Open weights
Yes
Reasoning
No
Tool calling
No

Sources and attribution

Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.

  • Epoch AIEpoch Capabilities Index, Epoch's own runs and the external results it collects.CC BY 4.0 · Retrieved Nov 12, 2026 · Data through Nov 9, 2026Epoch AI, ‘Capabilities & benchmarking’. Published online at epoch.ai. Retrieved from https://epoch.ai/benchmarks.
  • models.devSpecs and list prices per provider.MIT · Retrieved Nov 12, 2026models.dev, an open catalog of AI models (github.com/anomalyco/models.dev).
  • TokscaleActive users, tokens and token mix from public Tokscale submissions. Hidden accounts are excluded.How we count
Llama 3.2 1B Instruct by Meta - Benchmarks, List Prices, Specs | Tokscale