gpt-oss-safeguard-20b vs Mercury 2
gpt-oss-safeguard-20b costs 2.5x less per output token than Mercury 2 ($0.30 vs $0.75 per million). Updated October 23, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.30
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.75
gpt-oss-safeguard-20b or Mercury 2: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick gpt-oss-safeguard-20b for output tokens 2.5x cheaper ($0.30 vs $0.75 per million) and a larger context window (131K against 128K tokens).
No benchmark has tested both yet. gpt-oss-safeguard-20b has none yet; Mercury 2 on LMArena WebDev, AA Coding Index and SciCode. 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 Mercury 2 has a AA Intelligence Index result, 10.8.
Directional only
Agentic work
AA Agentic Index
No call
Only Mercury 2 has a AA Agentic Index result, 1.6.
Directional only
Web design
Design Arena: websites
No call
Only Mercury 2 has a Design Arena: websites result, 1036.
Directional only
Long documents
Listed context window
gpt-oss-safeguard-20b
gpt-oss-safeguard-20b takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-safeguard-20b
gpt-oss-safeguard-20b $0.0002, Mercury 2 $0.0006 per turn.
List prices
At a glance
- Coding index
- gpt-oss-safeguard-20b not benchmarked, Mercury 2 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-oss-safeguard-20b $0.30 against Mercury 2 $0.75 per million output tokens, 2.5x apart.
- Context window
- gpt-oss-safeguard-20b takes 131K tokens, Mercury 2 128K.
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 Index10 boards measured
| Benchmark | gpt-oss-safeguard-20b | Mercury 2 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1171 | Only Mercury 2 measured |
| AA Coding Index | Not measured | 31.1 | Only Mercury 2 measured |
| SciCode | Not measured | 37.7% | Only Mercury 2 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 26.5% | Only Mercury 2 measured |
| WeirdML | Not measured | 43.2% | Only Mercury 2 measured |
| ALE-Bench | Not measured | 785.6 | Only Mercury 2 measured |
| LMArena Text: coding | Not measured | 1390 | Only Mercury 2 measured |
| LMArena Text: software and IT | Not measured | 1385 | Only Mercury 2 measured |
| LMArena WebDev: React | Not measured | 1160 | Only Mercury 2 measured |
| LMArena WebDev: HTML | Not measured | 1199 | Only Mercury 2 measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | gpt-oss-safeguard-20b | Mercury 2 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 10.8 | Only Mercury 2 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | gpt-oss-safeguard-20b | Mercury 2 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.6 | Only Mercury 2 measured |
| τ²-Bench Telecom | Not measured | 70.8% | Only Mercury 2 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | gpt-oss-safeguard-20b | Mercury 2 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 77.0% | Only Mercury 2 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 17.1% | Only Mercury 2 measured |
| LMArena Text: hard prompts | Not measured | 1361 | Only Mercury 2 measured |
| LMArena Text: expert | Not measured | 1358 | Only Mercury 2 measured |
| LMArena Text: hard prompts in English | Not measured | 1373 | Only Mercury 2 measured |
| Neither model has a result on the other 18 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | gpt-oss-safeguard-20b | Mercury 2 | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1344 | Only Mercury 2 measured |
| LMArena Text: medicine and healthcare | Not measured | 1363 | Only Mercury 2 measured |
| LMArena Text: business and finance | Not measured | 1349 | Only Mercury 2 measured |
| Neither model has a result on the other 17 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | gpt-oss-safeguard-20b | Mercury 2 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1036 | Only Mercury 2 measured |
| Design Arena: UI components | Not measured | 996 | Only Mercury 2 measured |
| Design Arena: game dev | Not measured | 983 | Only Mercury 2 measured |
| Design Arena: data viz | Not measured | 1010 | Only Mercury 2 measured |
| Design Arena: 3D | Not measured | 983 | Only Mercury 2 measured |
| Design Arena: all code categories | Not measured | 1020 | Only Mercury 2 measured |
| Design Arena: SVG | Not measured | 997 | Only Mercury 2 measured |
| Design Arena: ASCII art | Not measured | 988 | Only Mercury 2 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index13 boards measured
| Benchmark | gpt-oss-safeguard-20b | Mercury 2 | Leader |
|---|---|---|---|
| IFBench | Not measured | 69.8% | Only Mercury 2 measured |
| Long context reasoning (AA-LCR) | Not measured | 43.7% | Only Mercury 2 measured |
| LMArena Text | Not measured | 1355 | Only Mercury 2 measured |
| LMArena Text: instruction following | Not measured | 1327 | Only Mercury 2 measured |
| LMArena Text: creative writing | Not measured | 1289 | Only Mercury 2 measured |
| LMArena Text: English | Not measured | 1378 | Only Mercury 2 measured |
| LMArena Text: non-English | Not measured | 1331 | Only Mercury 2 measured |
| LMArena Text: Chinese | Not measured | 1417 | Only Mercury 2 measured |
| LMArena Text: Russian | Not measured | 1304 | Only Mercury 2 measured |
| LMArena Text: multi-turn | Not measured | 1357 | Only Mercury 2 measured |
| LMArena Text: longer queries | Not measured | 1330 | Only Mercury 2 measured |
| LMArena Text: writing and language | Not measured | 1303 | Only Mercury 2 measured |
| LMArena Text: entertainment and media | Not measured | 1315 | Only Mercury 2 measured |
| Neither model has a result on the other 35 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-oss-safeguard-20b costs less
Repository review
50K input + 3K output tokens
gpt-oss-safeguard-20b costs less
Agent loop
200K input + 10K output tokens
gpt-oss-safeguard-20b 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-oss-safeguard-20b | Inception Mercury 2 |
|---|---|---|
| Maker | OpenAI | Inception |
| Weights | Open weights | No public weights listed |
| Released | October 29, 2025 | March 4, 2026 |
| Context window | 131K | 128K |
| Input $/Mtok | $0.075 | $0.25 |
| Output $/Mtok | $0.30 | $0.75 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is gpt-oss-safeguard-20b better than Mercury 2 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick gpt-oss-safeguard-20b for output tokens 2.5x cheaper ($0.30 vs $0.75 per million) and a larger context window (131K against 128K tokens).
Which is cheaper, gpt-oss-safeguard-20b or Mercury 2?
gpt-oss-safeguard-20b costs $0.075 per million input tokens and $0.30 per million output tokens; Mercury 2 costs $0.25 and $0.75. Cost per solved task is known for neither of them.
Which has the bigger context window, gpt-oss-safeguard-20b or Mercury 2?
gpt-oss-safeguard-20b, with 131K tokens against 128K.
Has any benchmark tested both gpt-oss-safeguard-20b and Mercury 2?
No benchmark has tested both yet. gpt-oss-safeguard-20b has none yet; Mercury 2 on LMArena WebDev, AA Coding Index and SciCode. Compare them on price and context instead. Data as of October 23, 2026.