Seed-2.0-Code vs GPT-5.4 Mini
Seed-2.0-Code costs 1.5x less per output token than GPT-5.4 Mini ($3.00 vs $4.50 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $3.00
- Coding
- 35.8
- Overall
- 44.0
- Output $/M
- $4.50
Seed-2.0-Code or GPT-5.4 Mini: which to pick
Only GPT-5.4 Mini has a coding score, 35.8 on the Vibe Coding Index; Seed-2.0-Code has none, so the two cannot be ranked on coding.
Pick Seed-2.0-Code for output tokens 1.5x cheaper ($3.00 vs $4.50 per million).
No benchmark has tested both yet. Seed-2.0-Code has none yet; GPT-5.4 Mini on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI). 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
Only GPT-5.4 Mini has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only GPT-5.4 Mini has a AA Intelligence Index result, 24.1.
Directional only
Agentic work
AA Agentic Index
No call
Only GPT-5.4 Mini has a AA Agentic Index result, 17.9.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.4 Mini has a GPQA Diamond result, 83.1%.
Directional only
Math
AIME
No call
Only GPT-5.4 Mini has a AIME result, 95.6%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.4 Mini has a MMLU Pro result, 84.5%.
Directional only
Long documents
Listed context window
GPT-5.4 Mini
GPT-5.4 Mini takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Seed-2.0-Code
Seed-2.0-Code $0.0020, GPT-5.4 Mini $0.0030 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.4 Mini has the number, $0.70.
Directional only
At a glance
- Coding index
- Seed-2.0-Code not benchmarked, GPT-5.4 Mini 35.8 from 5 benchmarks.
- 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
- Seed-2.0-Code $3.00 against GPT-5.4 Mini $4.50 per million output tokens, 1.5x apart.
- Context window
- Seed-2.0-Code takes 262K tokens, GPT-5.4 Mini 400K.
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 Index18 boards measured
| Benchmark | Seed-2.0-Code | GPT-5.4 Mini | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1397 | Only GPT-5.4 Mini measured |
| AA Coding Index | Not measured | 56.1 | Only GPT-5.4 Mini measured |
| LiveCodeBench (Vals AI) | Not measured | 81.5% | Only GPT-5.4 Mini measured |
| SWE-bench Verified (Vals AI) | Not measured | 73.0% | Only GPT-5.4 Mini measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 2.5% | Only GPT-5.4 Mini measured |
| Vibe Code Bench (Vals AI) | Not measured | 48.0% | Only GPT-5.4 Mini measured |
| Code migration (Vals AI) | Not measured | 12.9% | Only GPT-5.4 Mini measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only GPT-5.4 Mini measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 54.7% | Only GPT-5.4 Mini measured |
| SciCode | Not measured | 52.1% | Only GPT-5.4 Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 52.3% | Only GPT-5.4 Mini measured |
| FrontierCode | Not measured | 27.0% | Only GPT-5.4 Mini measured |
| WeirdML | Not measured | 60.3% | Only GPT-5.4 Mini measured |
| ALE-Bench | Not measured | 1188.6 | Only GPT-5.4 Mini measured |
| LMArena Text: coding | Not measured | 1438 | Only GPT-5.4 Mini measured |
| LMArena Text: software and IT | Not measured | 1436 | Only GPT-5.4 Mini measured |
| LMArena WebDev: React | Not measured | 1386 | Only GPT-5.4 Mini measured |
| LMArena WebDev: HTML | Not measured | 1419 | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Seed-2.0-Code | GPT-5.4 Mini | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 24.1 | Only GPT-5.4 Mini measured |
| Epoch Capabilities Index | Not measured | 148.7 | Only GPT-5.4 Mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Seed-2.0-Code | GPT-5.4 Mini | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 17.9 | Only GPT-5.4 Mini measured |
| Finance Agent (Vals AI) | Not measured | 45.4% | Only GPT-5.4 Mini measured |
| Tax Agent Bench (Vals AI) | Not measured | 8.8% | Only GPT-5.4 Mini measured |
| Legal Research Bench (Vals AI) | Not measured | 12.5% | Only GPT-5.4 Mini measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 45.4% | Only GPT-5.4 Mini measured |
| τ²-Bench Telecom | Not measured | 83.3% | Only GPT-5.4 Mini measured |
| DeepResearch Bench | Not measured | 36.3% | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index15 boards measured
| Benchmark | Seed-2.0-Code | GPT-5.4 Mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 83.1% | Only GPT-5.4 Mini measured |
| MMMU Pro (Vals AI) | Not measured | 79.3% | Only GPT-5.4 Mini measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 87.5% | Only GPT-5.4 Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 28.1% | Only GPT-5.4 Mini measured |
| GPQA Diamond (Epoch AI run) | Not measured | 86.9% | Only GPT-5.4 Mini measured |
| ARC-AGI | Not measured | 63.7% | Only GPT-5.4 Mini measured |
| ARC-AGI-2 | Not measured | 18.9% | Only GPT-5.4 Mini measured |
| Chess puzzles | Not measured | 23.0% | Only GPT-5.4 Mini measured |
| Mystery game puzzles | Not measured | 11.0% | Only GPT-5.4 Mini measured |
| LMArena Text: hard prompts | Not measured | 1424 | Only GPT-5.4 Mini measured |
| LMArena Text: expert | Not measured | 1435 | Only GPT-5.4 Mini measured |
| LMArena Text: hard prompts in English | Not measured | 1420 | Only GPT-5.4 Mini measured |
| LMArena Vision: diagrams | Not measured | 1266 | Only GPT-5.4 Mini measured |
| LMArena Vision: homework | Not measured | 1285 | Only GPT-5.4 Mini measured |
| Kagi LLM Benchmark | Not measured | 37.9% | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 7 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Seed-2.0-Code | GPT-5.4 Mini | Leader |
|---|---|---|---|
| AIME | Not measured | 95.6% | Only GPT-5.4 Mini measured |
| OTIS Mock AIME | Not measured | 88.9% | Only GPT-5.4 Mini measured |
| FrontierMath, tiers 1 to 3 | Not measured | 51.2% | Only GPT-5.4 Mini measured |
| FrontierMath, tier 4 | Not measured | 9.8% | Only GPT-5.4 Mini measured |
| ProofBench | Not measured | 21.0% | Only GPT-5.4 Mini measured |
| LMArena Text: math | Not measured | 1418 | Only GPT-5.4 Mini measured |
| LMArena Text: mathematical work | Not measured | 1429 | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards measured
| Benchmark | Seed-2.0-Code | GPT-5.4 Mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.5% | Only GPT-5.4 Mini measured |
| CaseLaw (Vals AI) | Not measured | 51.7% | Only GPT-5.4 Mini measured |
| CorpFin (Vals AI) | Not measured | 60.9% | Only GPT-5.4 Mini measured |
| TaxEval (Vals AI) | Not measured | 71.2% | Only GPT-5.4 Mini measured |
| MortgageTax (Vals AI) | Not measured | 63.5% | Only GPT-5.4 Mini measured |
| SimpleQA Verified | Not measured | 29.4% | Only GPT-5.4 Mini measured |
| LMArena Text: science | Not measured | 1417 | Only GPT-5.4 Mini measured |
| LMArena Text: medicine and healthcare | Not measured | 1395 | Only GPT-5.4 Mini measured |
| LMArena Text: legal and government | Not measured | 1414 | Only GPT-5.4 Mini measured |
| LMArena Text: business and finance | Not measured | 1418 | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index30 boards measured
| Benchmark | Seed-2.0-Code | GPT-5.4 Mini | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 50.8% | Only GPT-5.4 Mini measured |
| Vals Multimodal Index | Not measured | 54.2% | Only GPT-5.4 Mini measured |
| IFBench | Not measured | 73.3% | Only GPT-5.4 Mini measured |
| Long context reasoning (AA-LCR) | Not measured | 77.0% | Only GPT-5.4 Mini measured |
| DTBench | Not measured | 80.0% | Only GPT-5.4 Mini measured |
| LMCA | Not measured | 40.8% | Only GPT-5.4 Mini measured |
| LMArena Text | Not measured | 1412 | Only GPT-5.4 Mini measured |
| LMArena Text: instruction following | Not measured | 1405 | Only GPT-5.4 Mini measured |
| LMArena Text: creative writing | Not measured | 1370 | Only GPT-5.4 Mini measured |
| LMArena Vision | Not measured | 1245 | Only GPT-5.4 Mini measured |
| LMArena Text: English | Not measured | 1412 | Only GPT-5.4 Mini measured |
| LMArena Text: non-English | Not measured | 1405 | Only GPT-5.4 Mini measured |
| LMArena Text: Chinese | Not measured | 1446 | Only GPT-5.4 Mini measured |
| LMArena Text: German | Not measured | 1408 | Only GPT-5.4 Mini measured |
| LMArena Text: Japanese | Not measured | 1375 | Only GPT-5.4 Mini measured |
| LMArena Text: Korean | Not measured | 1370 | Only GPT-5.4 Mini measured |
| LMArena Text: French | Not measured | 1441 | Only GPT-5.4 Mini measured |
| LMArena Text: Spanish | Not measured | 1405 | Only GPT-5.4 Mini measured |
| LMArena Text: Russian | Not measured | 1417 | Only GPT-5.4 Mini measured |
| LMArena Text: Polish | Not measured | 1415 | Only GPT-5.4 Mini measured |
| LMArena Text: multi-turn | Not measured | 1429 | Only GPT-5.4 Mini measured |
| LMArena Text: longer queries | Not measured | 1408 | Only GPT-5.4 Mini measured |
| LMArena Text: writing and language | Not measured | 1393 | Only GPT-5.4 Mini measured |
| LMArena Text: entertainment and media | Not measured | 1373 | Only GPT-5.4 Mini measured |
| LMArena Vision: English | Not measured | 1244 | Only GPT-5.4 Mini measured |
| LMArena Vision: Chinese | Not measured | 1286 | Only GPT-5.4 Mini measured |
| LMArena Vision: reading text | Not measured | 1253 | Only GPT-5.4 Mini measured |
| LMArena Vision: humor | Not measured | 1235 | Only GPT-5.4 Mini measured |
| LMArena Vision: recognizing things | Not measured | 1218 | Only GPT-5.4 Mini measured |
| LMArena Vision: creative writing | Not measured | 1222 | Only GPT-5.4 Mini measured |
| Neither model has a result on the other 16 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
Seed-2.0-Code costs less
Repository review
50K input + 3K output tokens
Seed-2.0-Code costs less
Agent loop
200K input + 10K output tokens
Seed-2.0-Code 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 | ByteDance Seed Seed-2.0-Code | OpenAI GPT-5.4 Mini |
|---|---|---|
| Maker | ByteDance Seed | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | August 12, 2026 | March 17, 2026 |
| Context window | 262K | 400K |
| Input $/Mtok | $0.50 | $0.75 |
| Output $/Mtok | $3.00 | $4.50 |
| Coding index | Not benchmarked | 35.8 |
| Independent measurements behind it | 0 | 5 |
| Cost per solved task | Not computable | $0.70 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Seed-2.0-Code better than GPT-5.4 Mini for coding?
Only GPT-5.4 Mini has a coding score, 35.8 on the Vibe Coding Index; Seed-2.0-Code has none, so the two cannot be ranked on coding. Pick Seed-2.0-Code for output tokens 1.5x cheaper ($3.00 vs $4.50 per million).
Which is cheaper, Seed-2.0-Code or GPT-5.4 Mini?
Seed-2.0-Code costs $0.50 per million input tokens and $3.00 per million output tokens; GPT-5.4 Mini costs $0.75 and $4.50. Cost per solved task is known for GPT-5.4 Mini only.
Which has the bigger context window, Seed-2.0-Code or GPT-5.4 Mini?
GPT-5.4 Mini, with 400K tokens against 262K.
Has any benchmark tested both Seed-2.0-Code and GPT-5.4 Mini?
No benchmark has tested both yet. Seed-2.0-Code has none yet; GPT-5.4 Mini on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI). Compare them on price and context instead. Data as of October 21, 2026.