LLM Reference

Gemma 2 2B Instruct

Released
2024-07-31
Last refreshed
2026-05-19
Status
Researched 24d ago
Open WeightsCommercial use with conditionsCodingClassification

Gemma 2 2B Instruct is worth evaluating for coding and classification when its provider route and context window match the workload.

Use it for

  • Teams evaluating coding and classification
  • Workloads that can use a 8k context window
  • Buyers comparing 1 tracked provider route

Do not use it for

  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Family
Gemma 2
Released
2024-07-31
Context
8k
Parameters
2B
Architecture
Decoder Only
Specialization
general
Openness
Open weights
License
GemmaCommercial use with conditions
Training
finetuned
Created by

Pioneering artificial intelligence research.

London, United Kingdom
Founded 2014
Website
Pricing
Output / 1M
-
Input / 1M
-

Cheapest of 1 route · NVIDIA NIM

About

Gemma 2 2B Instruct is Google DeepMind's Gemma 2 model. Weights are openly available for self-hosting and scores 36.8 on GPQA.

Gemma 2 2B Instruct is an open-weight model in the Gemma 2 family. The structured metadata tracks a 8k-token context window. This page tracks provider routes through NVIDIA NIM. Headline tracked benchmarks include Google-Proof Q&A 36.8, HellaSwag 85.9, and HumanEval 52.4.

Top use-case fit: coding, agents, and build tasks

Coding

1 relevant benchmark in the decision map.

Classification

2 relevant benchmarks in the decision map.

Provider price ladder

Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
NVIDIA NIM--
ServerlessPartial

Available via routers & gateways(1)

Capabilities

No model capability flags are currently sourced.

Benchmark peer barsfor Coding

Benchmark scores(4)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionSource
Google-Proof Q&A36.8diamondhttps://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard
HellaSwag85.910-shothttps://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard
HumanEval52.4pass@1https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard
Massive Multitask Language Understanding64.75-shothttps://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard

Migration checks

No linked migration route is available for this model yet.