Granite 4.0 Micro vs Mercury 2.5
Mercury 2.5 leads Granite 4.0 Micro on the Artificial Analysis Intelligence Index, 12.3 to 5.1, and Granite 4.0 Micro costs 1.3x less per output token ($0.112 vs $0.15 per million). Updated October 22, 2026; 3 benchmarks have a result for both.
Granite 4.0 Micro or Mercury 2.5: which to pick
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Granite 4.0 Micro has none, so the two cannot be ranked on coding.
Pick Granite 4.0 Micro for output tokens 1.3x cheaper ($0.112 vs $0.15 per million).
- Shared results
- 3
- Granite 4.0 Micro only
- 10
- Mercury 2.5 only
- 19
- Like-for-like categories
- 3 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
Only Mercury 2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Mercury 2.5
Mercury 2.5 leads, 12.3 against 5.1.
Same board, both measured
Long documents
Listed context window
Mercury 2.5
Mercury 2.5 takes 260K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Granite 4.0 Micro
Granite 4.0 Micro $0.0001, Mercury 2.5 $0.0001 per turn.
List prices
At a glance
- Coding index
- Granite 4.0 Micro not benchmarked, Mercury 2.5 1.6 from 2 benchmarks.
- Widest category
- General, 64.7 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Granite 4.0 Micro 7.0% against Mercury 2.5 71.7%, 64.7 points apart on a 0 to 100 scale.
- Output price
- Granite 4.0 Micro $0.112 against Mercury 2.5 $0.15 per million output tokens, 1.3x apart.
- Context window
- Granite 4.0 Micro takes 131K tokens, Mercury 2.5 260K.
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 | Mercury 2.5 | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 3 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index11 boards, none shared
| Benchmark | Granite 4.0 Micro | Mercury 2.5 | Leader |
|---|---|---|---|
| Terminal-Bench 4 (Vals AI) | Not measured | 0.0% | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | Not measured | 3.7% | Only Mercury 2.5 measured |
| Code migration (Vals AI) | Not measured | 4.5% | Only Mercury 2.5 measured |
| IOI (Vals AI) | Not measured | 2.4% | Only Mercury 2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 34.5% | Only Mercury 2.5 measured |
| SkillsBench (Vals AI) | Not measured | 18.1% | Only Mercury 2.5 measured |
| CyberBench (Vals AI) | Not measured | 45.5% | Only Mercury 2.5 measured |
| LiveCodeBench (Artificial Analysis run) | 18.0% | Not measured | Only Granite 4.0 Micro measured |
| SciCode | Not measured | 38.5% | Only Mercury 2.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 1.5% | Not measured | Only Granite 4.0 Micro measured |
| ALE-Bench | Not measured | 301.6 | Only Mercury 2.5 measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Granite 4.0 Micro | Mercury 2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.1 | 12.3 | Mercury 2.5 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Granite 4.0 Micro | Mercury 2.5 | Leader |
|---|---|---|---|
| Finance Agent (Vals AI) | Not measured | 18.9% | Only Mercury 2.5 measured |
| Tax Agent Bench (Vals AI) | Not measured | 2.5% | Only Mercury 2.5 measured |
| Legal Research Bench (Vals AI) | Not measured | 4.3% | Only Mercury 2.5 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 8.8% | Only Mercury 2.5 measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 0.0% | Only Mercury 2.5 measured |
| τ²-Bench Telecom | 12.6% | Not measured | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Granite 4.0 Micro | Mercury 2.5 | 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% | 11.8% | Mercury 2.5 |
| GPQA Diamond (Epoch AI run) | 28.3% | Not measured | Only Granite 4.0 Micro measured |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Granite 4.0 Micro | Mercury 2.5 | 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 |
| ProofBench | Not measured | 3.0% | Only Mercury 2.5 measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Granite 4.0 Micro | Mercury 2.5 | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | Not measured | 83.1% | Only Mercury 2.5 measured |
| MedCode (Vals AI) | Not measured | 31.3% | Only Mercury 2.5 measured |
| 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 | Mercury 2.5 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Granite 4.0 Micro | Mercury 2.5 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | Not measured | 45.3% | Only Mercury 2.5 measured |
| MedScribe (Vals AI) | Not measured | 55.1% | Only Mercury 2.5 measured |
| IFBench | 24.8% | Not measured | Only Granite 4.0 Micro measured |
| Long context reasoning (AA-LCR) | 7.0% | 71.7% | Mercury 2.5 |
| 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 | Mercury 2.5 | 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 | Inception Mercury 2.5 |
|---|---|---|
| Maker | IBM Granite | Inception |
| Weights | Open weights | No public weights listed |
| Released | October 20, 2025 | September 8, 2026 |
| Context window | 131K | 260K |
| Input $/Mtok | $0.017 | $0.04 |
| Output $/Mtok | $0.112 | $0.15 |
| Coding index | Not benchmarked | 1.6 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Granite 4.0 Micro better than Mercury 2.5 for coding?
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Granite 4.0 Micro has none, so the two cannot be ranked on coding. Pick Granite 4.0 Micro for output tokens 1.3x cheaper ($0.112 vs $0.15 per million).
Which is cheaper, Granite 4.0 Micro or Mercury 2.5?
Granite 4.0 Micro costs $0.017 per million input tokens and $0.112 per million output tokens; Mercury 2.5 costs $0.04 and $0.15. Cost per solved task is known for neither of them.
Which has the bigger context window, Granite 4.0 Micro or Mercury 2.5?
Mercury 2.5, with 260K tokens against 131K.
How many benchmarks is the Granite 4.0 Micro vs Mercury 2.5 comparison based on?
3 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 Mercury 2.5's on 2. Where only one model has a result, the page says so instead of naming a winner.