GPT-4o vs Granite 4.0 Micro
Granite 4.0 Micro costs 89.3x less per output token than GPT-4o ($0.112 vs $10.00 per million). Updated October 22, 2026; 10 benchmarks have a result for both.
GPT-4o or Granite 4.0 Micro: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4o for work measured by Humanity's Last Exam (Artificial Analysis run), where it leads.
- Shared results
- 10
- GPT-4o only
- 18
- Granite 4.0 Micro only
- 3
- Like-for-like categories
- 6 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
No call
Only Granite 4.0 Micro has a AA Intelligence Index result, 5.1.
Directional only
Web design
Design Arena: websites
No call
Only GPT-4o has a Design Arena: websites result, 831.
Directional only
Long documents
Listed context window
Granite 4.0 Micro
Granite 4.0 Micro takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Granite 4.0 Micro
GPT-4o $0.0075, Granite 4.0 Micro $0.0001 per turn.
List prices
At a glance
- Coding index
- GPT-4o not benchmarked, Granite 4.0 Micro not benchmarked.
- Widest category
- Knowledge, 30.1 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): GPT-4o 49.3% against Granite 4.0 Micro 7.0%, 42.3 points apart on a 0 to 100 scale.
- Output price
- GPT-4o $10.00 against Granite 4.0 Micro $0.112 per million output tokens, 89.3x apart.
- Context window
- GPT-4o takes 128K tokens, Granite 4.0 Micro 131K.
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 | GPT-4o | Bars | Granite 4.0 Micro | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 1 | 1 | ||
| Math | 0 | 0 | 2 ties | |
| Knowledge | 1 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 7 | 1 | 2 ties |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | GPT-4o | Granite 4.0 Micro | Leader |
|---|---|---|---|
| SWE-bench Verified | 38.8% | Not measured | Only GPT-4o measured |
| SWE-bench Lite | 38.0% | Not measured | Only GPT-4o measured |
| SWE-bench (full test set) | 18.8% | Not measured | Only GPT-4o measured |
| SWE-bench Multimodal | 30.4% | Not measured | Only GPT-4o measured |
| LiveCodeBench (Artificial Analysis run) | 30.9% | 18.0% | GPT-4o |
| Terminal-Bench Hard (Artificial Analysis run) | 8.3% | 1.5% | GPT-4o |
| SciCode | 1.5% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-4o | Granite 4.0 Micro | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 5.1 | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-4o | Granite 4.0 Micro | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 25.1% | 12.6% | GPT-4o |
| GDPval | 9.9% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-4o | Granite 4.0 Micro | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 54.3% | 33.6% | GPT-4o |
| Humanity's Last Exam (Artificial Analysis run) | 2.4% | 5.0% | Granite 4.0 Micro |
| GPQA Diamond (Epoch AI run) | Not measured | 28.3% | Only Granite 4.0 Micro measured |
| ARC-AGI | 4.5% | Not measured | Only GPT-4o measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 18 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index00
| Benchmark | GPT-4o | Granite 4.0 Micro | Leader |
|---|---|---|---|
| AA Math Index | 6.0 | 6.0 | Tie |
| AIME 2025 (Artificial Analysis run) | 6.0% | 6.0% | Tie |
| OTIS Mock AIME | Not measured | 2.8% | Only Granite 4.0 Micro measured |
| MathArena | 3.6% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-4o | Granite 4.0 Micro | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 74.8% | 44.7% | GPT-4o |
| MMLU | 88.1% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 18 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4o | Granite 4.0 Micro | Leader |
|---|---|---|---|
| Design Arena: websites | 831 | Not measured | Only GPT-4o measured |
| Design Arena: UI components | 883 | Not measured | Only GPT-4o measured |
| Design Arena: game dev | 906 | Not measured | Only GPT-4o measured |
| Design Arena: data viz | 858 | Not measured | Only GPT-4o measured |
| Design Arena: 3D | 868 | Not measured | Only GPT-4o measured |
| Design Arena: all code categories | 860 | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-4o | Granite 4.0 Micro | Leader |
|---|---|---|---|
| IFBench | 34.3% | 24.8% | GPT-4o |
| Long context reasoning (AA-LCR) | 49.3% | 7.0% | GPT-4o |
| DTBench | 64.5% | Not measured | Only GPT-4o measured |
| LMCA | 16.6% | Not measured | Only GPT-4o 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 | GPT-4o | Granite 4.0 Micro | 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 | OpenAI GPT-4o | IBM Granite 4.0 Micro |
|---|---|---|
| Maker | OpenAI | IBM Granite |
| Weights | No public weights listed | Open weights |
| Released | May 13, 2024 | October 20, 2025 |
| Context window | 128K | 131K |
| Input $/Mtok | $2.50 | $0.017 |
| Output $/Mtok | $10.00 | $0.112 |
| 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 GPT-4o better than Granite 4.0 Micro for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4o for work measured by Humanity's Last Exam (Artificial Analysis run), where it leads.
Which is cheaper, GPT-4o or Granite 4.0 Micro?
GPT-4o costs $2.50 per million input tokens and $10.00 per million output tokens; Granite 4.0 Micro costs $0.017 and $0.112. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o or Granite 4.0 Micro?
Granite 4.0 Micro, with 131K tokens against 128K.
How many benchmarks is the GPT-4o vs Granite 4.0 Micro comparison based on?
10 benchmarks have a result for both models as of October 22, 2026. GPT-4o's coding index rests on 0 independent benchmarks and Granite 4.0 Micro's on 0. Where only one model has a result, the page says so instead of naming a winner.