GPT-4.1 Nano vs Palmyra X5
GPT-4.1 Nano costs 15.0x less per output token than Palmyra X5 ($0.40 vs $6.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- 24.7
- Output $/M
- $0.40
- Coding
- No data
- Overall
- No data
- Output $/M
- $6.00
GPT-4.1 Nano or Palmyra X5: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-4.1 Nano for output tokens 15.0x cheaper ($0.40 vs $6.00 per million) and a larger context window (1.05M against 1.04M tokens).
No benchmark has tested both yet. GPT-4.1 Nano has results on Aider polyglot, AA Coding Index and LiveCodeBench (Vals AI); Palmyra X5 has none yet. Compare them on price and context instead.
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 GPT-4.1 Nano has a AA Intelligence Index result, 7.8.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-4.1 Nano has a GPQA Diamond result, 50.8%.
Directional only
Math
AIME
No call
Only GPT-4.1 Nano has a AIME result, 26.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4.1 Nano has a MMLU Pro result, 63.5%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-4.1 Nano has a Design Arena: websites result, 973.
Directional only
Long documents
Listed context window
GPT-4.1 Nano
GPT-4.1 Nano takes 1.05M tokens against 1.04M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-4.1 Nano
GPT-4.1 Nano $0.0003, Palmyra X5 $0.0036 per turn.
List prices
At a glance
- Coding index
- GPT-4.1 Nano not benchmarked, Palmyra X5 not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-4.1 Nano $0.40 against Palmyra X5 $6.00 per million output tokens, 15.0x apart.
- Context window
- GPT-4.1 Nano takes 1.05M tokens, Palmyra X5 1.04M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards measured
| Benchmark | GPT-4.1 Nano | Palmyra X5 | Leader |
|---|---|---|---|
| Aider polyglot | 8.9% | Not measured | Only GPT-4.1 Nano measured |
| AA Coding Index | 11.1 | Not measured | Only GPT-4.1 Nano measured |
| LiveCodeBench (Vals AI) | 42.7% | Not measured | Only GPT-4.1 Nano measured |
| LiveCodeBench (Artificial Analysis run) | 32.6% | Not measured | Only GPT-4.1 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 3.8% | Not measured | Only GPT-4.1 Nano measured |
| WeirdML | 19.0% | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: coding | 1306 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: software and IT | 1305 | Not measured | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-4.1 Nano | Palmyra X5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.8 | Not measured | Only GPT-4.1 Nano measured |
| Epoch Capabilities Index | 129.5 | Not measured | Only GPT-4.1 Nano measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-4.1 Nano | Palmyra X5 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 17.3% | Not measured | Only GPT-4.1 Nano measured |
| Berkeley Function Calling Leaderboard (BFCL) | 33.1% | Not measured | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index12 boards measured
| Benchmark | GPT-4.1 Nano | Palmyra X5 | Leader |
|---|---|---|---|
| GPQA Diamond | 50.8% | Not measured | Only GPT-4.1 Nano measured |
| MMMU Pro (Vals AI) | 55.0% | Not measured | Only GPT-4.1 Nano measured |
| GPQA Diamond (Artificial Analysis run) | 51.2% | Not measured | Only GPT-4.1 Nano measured |
| Humanity's Last Exam (Artificial Analysis run) | 3.8% | Not measured | Only GPT-4.1 Nano measured |
| GPQA Diamond (Epoch AI run) | 48.9% | Not measured | Only GPT-4.1 Nano measured |
| ARC-AGI | 0.0% | Not measured | Only GPT-4.1 Nano measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4.1 Nano measured |
| Chess puzzles | 0.0% | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: hard prompts | 1286 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: expert | 1271 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: hard prompts in English | 1293 | Not measured | Only GPT-4.1 Nano measured |
| Kagi LLM Benchmark | 33.3% | Not measured | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | GPT-4.1 Nano | Palmyra X5 | Leader |
|---|---|---|---|
| AIME | 26.5% | Not measured | Only GPT-4.1 Nano measured |
| MATH 500 (Vals AI) | 80.2% | Not measured | Only GPT-4.1 Nano measured |
| MGSM (Vals AI) | 69.3% | Not measured | Only GPT-4.1 Nano measured |
| AA Math Index | 24.0 | Not measured | Only GPT-4.1 Nano measured |
| AIME 2025 (Artificial Analysis run) | 24.0% | Not measured | Only GPT-4.1 Nano measured |
| OTIS Mock AIME | 28.9% | Not measured | Only GPT-4.1 Nano measured |
| MATH level 5 | 70.0% | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: math | 1274 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: mathematical work | 1274 | Not measured | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards measured
| Benchmark | GPT-4.1 Nano | Palmyra X5 | Leader |
|---|---|---|---|
| MMLU Pro | 63.5% | Not measured | Only GPT-4.1 Nano measured |
| LegalBench (Vals AI) | 61.1% | Not measured | Only GPT-4.1 Nano measured |
| CorpFin (Vals AI) | 42.1% | Not measured | Only GPT-4.1 Nano measured |
| TaxEval (Vals AI) | 60.8% | Not measured | Only GPT-4.1 Nano measured |
| MortgageTax (Vals AI) | 52.8% | Not measured | Only GPT-4.1 Nano measured |
| MedQA (Vals AI) | 68.2% | Not measured | Only GPT-4.1 Nano measured |
| MMLU Pro (Artificial Analysis run) | 65.7% | Not measured | Only GPT-4.1 Nano measured |
| SimpleQA Verified | 6.0% | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: science | 1297 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: medicine and healthcare | 1276 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: legal and government | 1300 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: business and finance | 1267 | Not measured | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | GPT-4.1 Nano | Palmyra X5 | Leader |
|---|---|---|---|
| Design Arena: websites | 973 | Not measured | Only GPT-4.1 Nano measured |
| Design Arena: UI components | 913 | Not measured | Only GPT-4.1 Nano measured |
| Design Arena: game dev | 970 | Not measured | Only GPT-4.1 Nano measured |
| Design Arena: data viz | 891 | Not measured | Only GPT-4.1 Nano measured |
| Design Arena: 3D | 924 | Not measured | Only GPT-4.1 Nano measured |
| Design Arena: all code categories | 962 | Not measured | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 3 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index20 boards measured
| Benchmark | GPT-4.1 Nano | Palmyra X5 | Leader |
|---|---|---|---|
| IFBench | 32.0% | Not measured | Only GPT-4.1 Nano measured |
| Long context reasoning (AA-LCR) | 20.3% | Not measured | Only GPT-4.1 Nano measured |
| DTBench | 52.5% | Not measured | Only GPT-4.1 Nano measured |
| LMCA | 5.5% | Not measured | Only GPT-4.1 Nano measured |
| Fiction.LiveBench | 25.0% | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text | 1285 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: instruction following | 1266 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: creative writing | 1260 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Vision | 1063 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: English | 1303 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: non-English | 1260 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: Chinese | 1270 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: German | 1288 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: Japanese | 1198 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: Russian | 1261 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: multi-turn | 1277 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: longer queries | 1283 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: writing and language | 1261 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Text: entertainment and media | 1243 | Not measured | Only GPT-4.1 Nano measured |
| LMArena Vision: English | 1101 | Not measured | Only GPT-4.1 Nano measured |
| Neither model has a result on the other 28 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
GPT-4.1 Nano costs less
Repository review
50K input + 3K output tokens
GPT-4.1 Nano costs less
Agent loop
200K input + 10K output tokens
GPT-4.1 Nano 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-4.1 Nano | Writer Palmyra X5 |
|---|---|---|
| Maker | OpenAI | Writer |
| Weights | No public weights listed | No public weights listed |
| Released | April 14, 2025 | January 21, 2026 |
| Context window | 1.05M | 1.04M |
| Input $/Mtok | $0.10 | $0.60 |
| Output $/Mtok | $0.40 | $6.00 |
| 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-4.1 Nano better than Palmyra X5 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-4.1 Nano for output tokens 15.0x cheaper ($0.40 vs $6.00 per million) and a larger context window (1.05M against 1.04M tokens).
Which is cheaper, GPT-4.1 Nano or Palmyra X5?
GPT-4.1 Nano costs $0.10 per million input tokens and $0.40 per million output tokens; Palmyra X5 costs $0.60 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4.1 Nano or Palmyra X5?
GPT-4.1 Nano, with 1.05M tokens against 1.04M.
Has any benchmark tested both GPT-4.1 Nano and Palmyra X5?
No benchmark has tested both yet. GPT-4.1 Nano has results on Aider polyglot, AA Coding Index and LiveCodeBench (Vals AI); Palmyra X5 has none yet. Compare them on price and context instead. Data as of October 22, 2026.