Granite 4.0 Micro vs o3 Mini High
o3 Mini High leads Granite 4.0 Micro on the Artificial Analysis Intelligence Index, 11.0 to 5.1, and Granite 4.0 Micro costs 39.3x less per output token ($0.112 vs $4.40 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
Granite 4.0 Micro or o3 Mini High: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Granite 4.0 Micro for output tokens 39.3x cheaper ($0.112 vs $4.40 per million) and work measured by AA Intelligence Index, where it leads.
- Shared results
- 1
- Granite 4.0 Micro only
- 12
- o3 Mini High only
- 2
- 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
o3 Mini High
o3 Mini High leads, 11.0 against 5.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only o3 Mini High has a AA Agentic Index result, 0.9.
Directional only
Long documents
Listed context window
o3 Mini High
o3 Mini High takes 200K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Granite 4.0 Micro
Granite 4.0 Micro $0.0001, o3 Mini High $0.0033 per turn.
List prices
At a glance
- Coding index
- Granite 4.0 Micro not benchmarked, o3 Mini High not benchmarked.
- Widest category
- Intelligence, 5.9 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: Granite 4.0 Micro 5.1 against o3 Mini High 11.0, 5.9 points apart on a 0 to 100 scale.
- Output price
- Granite 4.0 Micro $0.112 against o3 Mini High $4.40 per million output tokens, 39.3x apart.
- Context window
- Granite 4.0 Micro takes 131K tokens, o3 Mini High 200K.
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 | Granite 4.0 Micro | Bars | o3 Mini High | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards, none shared
| Benchmark | Granite 4.0 Micro | o3 Mini High | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 16.3 | Only o3 Mini High measured |
| LiveCodeBench (Artificial Analysis run) | 18.0% | Not measured | Only Granite 4.0 Micro measured |
| Terminal-Bench Hard (Artificial Analysis run) | 1.5% | Not measured | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Granite 4.0 Micro | o3 Mini High | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.1 | 11.0 | o3 Mini High |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Granite 4.0 Micro | o3 Mini High | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.9 | Only o3 Mini High measured |
| τ²-Bench Telecom | 12.6% | Not measured | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Granite 4.0 Micro | o3 Mini High | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 33.6% | Not measured | Only Granite 4.0 Micro measured |
| Humanity's Last Exam (Artificial Analysis run) | 5.0% | Not measured | Only Granite 4.0 Micro measured |
| GPQA Diamond (Epoch AI run) | 28.3% | Not measured | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Granite 4.0 Micro | o3 Mini High | Leader |
|---|---|---|---|
| AA Math Index | 6.0 | Not measured | Only Granite 4.0 Micro measured |
| AIME 2025 (Artificial Analysis run) | 6.0% | Not measured | Only Granite 4.0 Micro measured |
| OTIS Mock AIME | 2.8% | Not measured | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Granite 4.0 Micro | o3 Mini High | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 44.7% | Not measured | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 17 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Granite 4.0 Micro | o3 Mini High | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Granite 4.0 Micro | o3 Mini High | Leader |
|---|---|---|---|
| IFBench | 24.8% | Not measured | Only Granite 4.0 Micro measured |
| Long context reasoning (AA-LCR) | 7.0% | Not measured | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Granite 4.0 Micro | o3 Mini High | 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
Granite 4.0 Micro costs less
Repository review
50K input + 3K output tokens
Granite 4.0 Micro costs less
Agent loop
200K input + 10K output tokens
Granite 4.0 Micro 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 | IBM Granite 4.0 Micro | OpenAI o3 Mini High |
|---|---|---|
| Maker | IBM Granite | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | October 20, 2025 | February 12, 2025 |
| Context window | 131K | 200K |
| Input $/Mtok | $0.017 | $1.10 |
| Output $/Mtok | $0.112 | $4.40 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Granite 4.0 Micro better than o3 Mini High for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Granite 4.0 Micro for output tokens 39.3x cheaper ($0.112 vs $4.40 per million) and work measured by AA Intelligence Index, where it leads.
Which is cheaper, Granite 4.0 Micro or o3 Mini High?
Granite 4.0 Micro costs $0.017 per million input tokens and $0.112 per million output tokens; o3 Mini High costs $1.10 and $4.40. Cost per solved task is known for neither of them.
Which has the bigger context window, Granite 4.0 Micro or o3 Mini High?
o3 Mini High, with 200K tokens against 131K.
How many benchmarks is the Granite 4.0 Micro vs o3 Mini High comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. Granite 4.0 Micro's coding index rests on 0 independent benchmarks and o3 Mini High's on 0. Where only one model has a result, the page says so instead of naming a winner.