GPT-5.1-Codex-Max vs Mercury 2.5
Mercury 2.5 costs 66.7x less per output token than GPT-5.1-Codex-Max ($0.15 vs $10.00 per million). Updated October 21, 2026; 3 benchmarks have a result for both.
GPT-5.1-Codex-Max or Mercury 2.5: which to pick
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; GPT-5.1-Codex-Max has none, so the two cannot be ranked on coding.
Pick GPT-5.1-Codex-Max for a larger context window (400K against 260K tokens) and work measured by Vibe Code Bench (Vals AI) or ALE-Bench, where it leads.
- Shared results
- 3
- GPT-5.1-Codex-Max only
- 3
- Mercury 2.5 only
- 19
- Like-for-like categories
- 2 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
No call
Only Mercury 2.5 has a AA Intelligence Index result, 12.3.
Directional only
Long documents
Listed context window
GPT-5.1-Codex-Max
GPT-5.1-Codex-Max takes 400K tokens against 260K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
GPT-5.1-Codex-Max $0.0063, Mercury 2.5 $0.0001 per turn.
List prices
At a glance
- Coding index
- GPT-5.1-Codex-Max not benchmarked, Mercury 2.5 1.6 from 2 benchmarks.
- Widest category
- Coding, 24.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- ALE-Bench: GPT-5.1-Codex-Max 1228.3 against Mercury 2.5 301.6, 30.9 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex-Max $10.00 against Mercury 2.5 $0.15 per million output tokens, 66.7x apart.
- Context window
- GPT-5.1-Codex-Max takes 400K 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 | GPT-5.1-Codex-Max | Bars | Mercury 2.5 | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Math | 1 | 0 | ||
| All shared boards | 3 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | GPT-5.1-Codex-Max | Mercury 2.5 | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | 83.6% | Not measured | Only GPT-5.1-Codex-Max measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.0% | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | 22.2% | 3.7% | GPT-5.1-Codex-Max |
| 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 |
| SciCode | Not measured | 38.5% | Only Mercury 2.5 measured |
| Terminal-Bench | 60.4% | Not measured | Only GPT-5.1-Codex-Max measured |
| ALE-Bench | 1228.3 | 301.6 | GPT-5.1-Codex-Max |
| Neither model has a result on the other 28 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5.1-Codex-Max | Mercury 2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 12.3 | Only Mercury 2.5 measured |
| 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 | GPT-5.1-Codex-Max | 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 |
| METR time horizons | 70.8% | Not measured | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5.1-Codex-Max | Mercury 2.5 | Leader |
|---|---|---|---|
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 11.8% | Only Mercury 2.5 measured |
| Neither model has a result on the other 21 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex-Max | Mercury 2.5 | Leader |
|---|---|---|---|
| ProofBench | 9.0% | 3.0% | GPT-5.1-Codex-Max |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | 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 |
| Neither model has a result on the other 16 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | Mercury 2.5 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | 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 |
| Long context reasoning (AA-LCR) | Not measured | 71.7% | Only Mercury 2.5 measured |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.1-Codex-Max | 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
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 | OpenAI GPT-5.1-Codex-Max | Inception Mercury 2.5 |
|---|---|---|
| Maker | OpenAI | Inception |
| Weights | No public weights listed | No public weights listed |
| Released | December 4, 2025 | September 8, 2026 |
| Context window | 400K | 260K |
| Input $/Mtok | $1.25 | $0.04 |
| Output $/Mtok | $10.00 | $0.15 |
| Coding index | Not benchmarked | 1.6 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex-Max better than Mercury 2.5 for coding?
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; GPT-5.1-Codex-Max has none, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Max for a larger context window (400K against 260K tokens) and work measured by Vibe Code Bench (Vals AI) or ALE-Bench, where it leads.
Which is cheaper, GPT-5.1-Codex-Max or Mercury 2.5?
GPT-5.1-Codex-Max costs $1.25 per million input tokens and $10.00 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, GPT-5.1-Codex-Max or Mercury 2.5?
GPT-5.1-Codex-Max, with 400K tokens against 260K.
How many benchmarks is the GPT-5.1-Codex-Max vs Mercury 2.5 comparison based on?
3 benchmarks have a result for both models as of October 21, 2026. GPT-5.1-Codex-Max's coding index rests on 1 independent benchmark and Mercury 2.5's on 2. Where only one model has a result, the page says so instead of naming a winner.