Mercury 2.5 vs Phi 4
Mercury 2.5 leads Phi 4 on the Artificial Analysis Intelligence Index, 12.3 to 5.9, at about the same output price ($0.15 vs $0.14 per million). Updated October 21, 2026; 3 benchmarks have a result for both.
Mercury 2.5 or Phi 4: which to pick
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Phi 4 has none, so the two cannot be ranked on coding.
Pick Phi 4 for output tokens 1.1x cheaper ($0.14 vs $0.15 per million).
- Shared results
- 3
- Mercury 2.5 only
- 19
- Phi 4 only
- 43
- 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 5.9.
Same board, both measured
Long documents
Listed context window
Mercury 2.5
Mercury 2.5 takes 260K tokens against 16K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
Mercury 2.5 $0.0001, Phi 4 $0.0001 per turn.
List prices
At a glance
- Coding index
- Mercury 2.5 1.6 from 2 benchmarks, Phi 4 not benchmarked.
- Widest category
- General, 71.7 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Mercury 2.5 71.7% against Phi 4 0.0%, 71.7 points apart on a 0 to 100 scale.
- Output price
- Mercury 2.5 $0.15 against Phi 4 $0.14 per million output tokens, 1.1x apart.
- Context window
- Mercury 2.5 takes 260K tokens, Phi 4 16K.
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 | Mercury 2.5 | Bars | Phi 4 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 3 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index13 boards, none shared
| Benchmark | Mercury 2.5 | Phi 4 | Leader |
|---|---|---|---|
| Terminal-Bench 4 (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | 3.7% | Not measured | Only Mercury 2.5 measured |
| Code migration (Vals AI) | 4.5% | Not measured | Only Mercury 2.5 measured |
| IOI (Vals AI) | 2.4% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 34.5% | Not measured | Only Mercury 2.5 measured |
| SkillsBench (Vals AI) | 18.1% | Not measured | Only Mercury 2.5 measured |
| CyberBench (Vals AI) | 45.5% | Not measured | Only Mercury 2.5 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 23.1% | Only Phi 4 measured |
| SciCode | 38.5% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 3.8% | Only Phi 4 measured |
| ALE-Bench | 301.6 | Not measured | Only Mercury 2.5 measured |
| LMArena Text: coding | Not measured | 1231 | Only Phi 4 measured |
| LMArena Text: software and IT | Not measured | 1228 | Only Phi 4 measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2.5 | Phi 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.3 | 5.9 | Mercury 2.5 |
| Epoch Capabilities Index | Not measured | 130.5 | Only Phi 4 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mercury 2.5 | Phi 4 | Leader |
|---|---|---|---|
| Finance Agent (Vals AI) | 18.9% | Not measured | Only Mercury 2.5 measured |
| Tax Agent Bench (Vals AI) | 2.5% | Not measured | Only Mercury 2.5 measured |
| Legal Research Bench (Vals AI) | 4.3% | Not measured | Only Mercury 2.5 measured |
| Excel Modeling Benchmark (Vals AI) | 8.8% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| τ²-Bench Telecom | Not measured | 0.0% | Only Phi 4 measured |
| BALROG | Not measured | 11.6% | Only Phi 4 measured |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 28.8% | Only Phi 4 measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2.5 | Phi 4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 57.5% | Only Phi 4 measured |
| Humanity's Last Exam (Artificial Analysis run) | 11.8% | 3.8% | Mercury 2.5 |
| GPQA Diamond (Epoch AI run) | Not measured | 56.1% | Only Phi 4 measured |
| LMArena Text: hard prompts | Not measured | 1220 | Only Phi 4 measured |
| LMArena Text: expert | Not measured | 1203 | Only Phi 4 measured |
| LMArena Text: hard prompts in English | Not measured | 1230 | Only Phi 4 measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Mercury 2.5 | Phi 4 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 18.0 | Only Phi 4 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 18.0% | Only Phi 4 measured |
| OTIS Mock AIME | Not measured | 13.8% | Only Phi 4 measured |
| ProofBench | 3.0% | Not measured | Only Mercury 2.5 measured |
| MATH level 5 | Not measured | 64.9% | Only Phi 4 measured |
| LMArena Text: math | Not measured | 1246 | Only Phi 4 measured |
| LMArena Text: mathematical work | Not measured | 1254 | Only Phi 4 measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mercury 2.5 | Phi 4 | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.1% | Not measured | Only Mercury 2.5 measured |
| MedCode (Vals AI) | 31.3% | Not measured | Only Mercury 2.5 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 71.4% | Only Phi 4 measured |
| MMLU | Not measured | 84.8% | Only Phi 4 measured |
| LMArena Text: science | Not measured | 1206 | Only Phi 4 measured |
| LMArena Text: medicine and healthcare | Not measured | 1202 | Only Phi 4 measured |
| LMArena Text: legal and government | Not measured | 1241 | Only Phi 4 measured |
| LMArena Text: business and finance | Not measured | 1199 | Only Phi 4 measured |
| Neither model has a result on the other 10 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2.5 | Phi 4 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2.5 | Phi 4 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 45.3% | Not measured | Only Mercury 2.5 measured |
| MedScribe (Vals AI) | 55.1% | Not measured | Only Mercury 2.5 measured |
| IFBench | Not measured | 23.5% | Only Phi 4 measured |
| Long context reasoning (AA-LCR) | 71.7% | 0.0% | Mercury 2.5 |
| Creative writing (Lech Mazur) | Not measured | 62.6% | Only Phi 4 measured |
| LMArena Text | Not measured | 1217 | Only Phi 4 measured |
| LMArena Text: instruction following | Not measured | 1201 | Only Phi 4 measured |
| LMArena Text: creative writing | Not measured | 1181 | Only Phi 4 measured |
| LMArena Text: English | Not measured | 1231 | Only Phi 4 measured |
| LMArena Text: non-English | Not measured | 1197 | Only Phi 4 measured |
| LMArena Text: Chinese | Not measured | 1212 | Only Phi 4 measured |
| LMArena Text: German | Not measured | 1222 | Only Phi 4 measured |
| LMArena Text: Japanese | Not measured | 1158 | Only Phi 4 measured |
| LMArena Text: Korean | Not measured | 1151 | Only Phi 4 measured |
| LMArena Text: French | Not measured | 1224 | Only Phi 4 measured |
| LMArena Text: Spanish | Not measured | 1234 | Only Phi 4 measured |
| LMArena Text: Russian | Not measured | 1209 | Only Phi 4 measured |
| LMArena Text: multi-turn | Not measured | 1206 | Only Phi 4 measured |
| LMArena Text: longer queries | Not measured | 1217 | Only Phi 4 measured |
| LMArena Text: writing and language | Not measured | 1198 | Only Phi 4 measured |
| LMArena Text: entertainment and media | Not measured | 1162 | Only Phi 4 measured |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2.5 | Phi 4 | 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
Mercury 2.5 costs less
Repository review
50K input + 3K output tokens
Mercury 2.5 costs less
Agent loop
200K input + 10K output tokens
Mercury 2.5 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 | Inception Mercury 2.5 | Microsoft Phi 4 |
|---|---|---|
| Maker | Inception | Microsoft |
| Weights | No public weights listed | Open weights |
| Released | September 8, 2026 | January 10, 2025 |
| Context window | 260K | 16K |
| Input $/Mtok | $0.04 | $0.07 |
| Output $/Mtok | $0.15 | $0.14 |
| Coding index | 1.6 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2.5 better than Phi 4 for coding?
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Phi 4 has none, so the two cannot be ranked on coding. Pick Phi 4 for output tokens 1.1x cheaper ($0.14 vs $0.15 per million).
Which is cheaper, Mercury 2.5 or Phi 4?
Mercury 2.5 costs $0.04 per million input tokens and $0.15 per million output tokens; Phi 4 costs $0.07 and $0.14. Cost per solved task is known for neither of them.
Which has the bigger context window, Mercury 2.5 or Phi 4?
Mercury 2.5, with 260K tokens against 16K.
How many benchmarks is the Mercury 2.5 vs Phi 4 comparison based on?
3 benchmarks have a result for both models as of October 21, 2026. Mercury 2.5's coding index rests on 2 independent benchmarks and Phi 4's on 0. Where only one model has a result, the page says so instead of naming a winner.