GPT-5.1-Codex-Max vs ReMM SLERP 13B
ReMM SLERP 13B costs 15.4x less per output token than GPT-5.1-Codex-Max ($0.65 vs $10.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $10.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.65
GPT-5.1-Codex-Max or ReMM SLERP 13B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.1-Codex-Max for a larger context window (400K against 6K tokens).
No benchmark has tested both yet. GPT-5.1-Codex-Max has results on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench; ReMM SLERP 13B 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
Long documents
Listed context window
GPT-5.1-Codex-Max
GPT-5.1-Codex-Max takes 400K tokens against 6K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
ReMM SLERP 13B
GPT-5.1-Codex-Max $0.0063, ReMM SLERP 13B $0.0007 per turn.
List prices
At a glance
- Coding index
- GPT-5.1-Codex-Max not benchmarked, ReMM SLERP 13B 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-5.1-Codex-Max $10.00 against ReMM SLERP 13B $0.65 per million output tokens, 15.4x apart.
- Context window
- GPT-5.1-Codex-Max takes 400K tokens, ReMM SLERP 13B 6K.
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 Index4 boards measured
| Benchmark | GPT-5.1-Codex-Max | ReMM SLERP 13B | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | 83.6% | Not measured | Only GPT-5.1-Codex-Max measured |
| Vibe Code Bench (Vals AI) | 22.2% | Not measured | Only GPT-5.1-Codex-Max measured |
| Terminal-Bench | 60.4% | Not measured | Only GPT-5.1-Codex-Max measured |
| ALE-Bench | 1228.3 | Not measured | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 35 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5.1-Codex-Max | ReMM SLERP 13B | Leader |
|---|---|---|---|
| METR time horizons | 70.8% | Not measured | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 40 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-5.1-Codex-Max | ReMM SLERP 13B | Leader |
|---|---|---|---|
| ProofBench | 9.0% | Not measured | Only GPT-5.1-Codex-Max measured |
| Neither model has a result on the other 12 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
ReMM SLERP 13B costs less
Repository review
50K input + 3K output tokens
ReMM SLERP 13B costs less
Agent loop
200K input + 10K output tokens
ReMM SLERP 13B 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 | ReMM SLERP 13B |
|---|---|---|
| Maker | OpenAI | Undi95 |
| Weights | No public weights listed | Open weights |
| Released | December 4, 2025 | July 22, 2023 |
| Context window | 400K | 6K |
| Input $/Mtok | $1.25 | $0.35 |
| Output $/Mtok | $10.00 | $0.65 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex-Max better than ReMM SLERP 13B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Max for a larger context window (400K against 6K tokens).
Which is cheaper, GPT-5.1-Codex-Max or ReMM SLERP 13B?
GPT-5.1-Codex-Max costs $1.25 per million input tokens and $10.00 per million output tokens; ReMM SLERP 13B costs $0.35 and $0.65. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5.1-Codex-Max or ReMM SLERP 13B?
GPT-5.1-Codex-Max, with 400K tokens against 6K.
Has any benchmark tested both GPT-5.1-Codex-Max and ReMM SLERP 13B?
No benchmark has tested both yet. GPT-5.1-Codex-Max has results on LiveCodeBench (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench; ReMM SLERP 13B has none yet. Compare them on price and context instead. Data as of October 22, 2026.