Grok Build 0.1 vs Llama 3.2 1B Instruct
Grok Build 0.1 leads Llama 3.2 1B Instruct on the Artificial Analysis Intelligence Index, 27.2 to 4.8, and Llama 3.2 1B Instruct costs 10.0x less per output token ($0.201 vs $2.00 per million). Updated October 21, 2026; 1 benchmarks have a result for both.
Grok Build 0.1 or Llama 3.2 1B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Grok Build 0.1 for a larger context window (256K against 60K tokens).
- Shared results
- 1
- Grok Build 0.1 only
- 2
- Llama 3.2 1B Instruct only
- 37
- Like-for-like categories
- 1 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Grok Build 0.1
Grok Build 0.1 leads, 27.2 against 4.8.
Same board, both measured
Long documents
Listed context window
Grok Build 0.1
Grok Build 0.1 takes 256K tokens against 60K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.2 1B Instruct
Grok Build 0.1 $0.0020, Llama 3.2 1B Instruct $0.0001 per turn.
List prices
At a glance
- Coding index
- Grok Build 0.1 not benchmarked, Llama 3.2 1B Instruct not benchmarked.
- Widest category
- Intelligence, 22.4 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: Grok Build 0.1 27.2 against Llama 3.2 1B Instruct 4.8, 22.4 points apart on a 0 to 100 scale.
- Output price
- Grok Build 0.1 $2.00 against Llama 3.2 1B Instruct $0.201 per million output tokens, 10.0x apart.
- Context window
- Grok Build 0.1 takes 256K tokens, Llama 3.2 1B Instruct 60K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Grok Build 0.1 | Bars | Llama 3.2 1B Instruct | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| All shared boards | 1 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index6 boards, none shared
| Benchmark | Grok Build 0.1 | Llama 3.2 1B Instruct | Leader |
|---|---|---|---|
| AA Coding Index | 51.5 | Not measured | Only Grok Build 0.1 measured |
| Vibe Code Bench (Vals AI) | 13.4% | Not measured | Only Grok Build 0.1 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 1.9% | Only Llama 3.2 1B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 0.0% | Only Llama 3.2 1B Instruct measured |
| LMArena Text: coding | Not measured | 1070 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: software and IT | Not measured | 1056 | Only Llama 3.2 1B Instruct measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Grok Build 0.1 | Llama 3.2 1B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 27.2 | 4.8 | Grok Build 0.1 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Grok Build 0.1 | Llama 3.2 1B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 0.0% | Only Llama 3.2 1B Instruct measured |
| BALROG | Not measured | 6.6% | Only Llama 3.2 1B Instruct measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 10.8% | Only Llama 3.2 1B Instruct measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Grok Build 0.1 | Llama 3.2 1B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 19.6% | Only Llama 3.2 1B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 5.5% | Only Llama 3.2 1B Instruct measured |
| GPQA Diamond (Epoch AI run) | Not measured | 23.9% | Only Llama 3.2 1B Instruct measured |
| LMArena Text: hard prompts | Not measured | 1044 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: expert | Not measured | 1007 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: hard prompts in English | Not measured | 1087 | Only Llama 3.2 1B Instruct measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Grok Build 0.1 | Llama 3.2 1B Instruct | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 0.0 | Only Llama 3.2 1B Instruct measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 0.0% | Only Llama 3.2 1B Instruct measured |
| OTIS Mock AIME | Not measured | 0.6% | Only Llama 3.2 1B Instruct measured |
| LMArena Text: math | Not measured | 1086 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: mathematical work | Not measured | 1098 | Only Llama 3.2 1B Instruct measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Grok Build 0.1 | Llama 3.2 1B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 20.0% | Only Llama 3.2 1B Instruct measured |
| LMArena Text: science | Not measured | 1055 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: medicine and healthcare | Not measured | 1009 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: legal and government | Not measured | 1071 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: business and finance | Not measured | 1000 | Only Llama 3.2 1B Instruct measured |
| Neither model has a result on the other 13 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Grok Build 0.1 | Llama 3.2 1B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | Grok Build 0.1 | Llama 3.2 1B Instruct | Leader |
|---|---|---|---|
| IFBench | Not measured | 22.8% | Only Llama 3.2 1B Instruct measured |
| Long context reasoning (AA-LCR) | Not measured | 6.7% | Only Llama 3.2 1B Instruct measured |
| LMArena Text | Not measured | 1055 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: instruction following | Not measured | 1031 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: creative writing | Not measured | 1033 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: English | Not measured | 1117 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: non-English | Not measured | 973 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: Chinese | Not measured | 959 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: German | Not measured | 1014 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: Russian | Not measured | 941 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: multi-turn | Not measured | 1030 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: longer queries | Not measured | 1050 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: writing and language | Not measured | 1030 | Only Llama 3.2 1B Instruct measured |
| LMArena Text: entertainment and media | Not measured | 1025 | Only Llama 3.2 1B Instruct measured |
| Neither model has a result on the other 32 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Grok Build 0.1 | Llama 3.2 1B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Llama 3.2 1B Instruct costs less
Repository review
50K input + 3K output tokens
Llama 3.2 1B Instruct costs less
Agent loop
200K input + 10K output tokens
Llama 3.2 1B Instruct costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | SpaceXAI Grok Build 0.1 | Meta Llama 3.2 1B Instruct |
|---|---|---|
| Maker | xAI | Meta Llama |
| Weights | No public weights listed | Open weights |
| Released | May 20, 2026 | September 25, 2024 |
| Context window | 256K | 60K |
| Input $/Mtok | $1.00 | $0.027 |
| Output $/Mtok | $2.00 | $0.201 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Grok Build 0.1 better than Llama 3.2 1B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Grok Build 0.1 for a larger context window (256K against 60K tokens).
Which is cheaper, Grok Build 0.1 or Llama 3.2 1B Instruct?
Grok Build 0.1 costs $1.00 per million input tokens and $2.00 per million output tokens; Llama 3.2 1B Instruct costs $0.027 and $0.201. Cost per solved task is known for neither of them.
Which has the bigger context window, Grok Build 0.1 or Llama 3.2 1B Instruct?
Grok Build 0.1, with 256K tokens against 60K.
How many benchmarks is the Grok Build 0.1 vs Llama 3.2 1B Instruct comparison based on?
1 benchmarks have a result for both models as of October 21, 2026. Grok Build 0.1's coding index rests on 1 independent benchmark and Llama 3.2 1B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.