Models / claude-sonnet-5
Claude Sonnet 5
Anthropic's model, with closed weights. Forcebench has run it in 4 configurations on the API board. API is models reached through a hosted service; Local, models served on Forcebench’s own hardware.
On the API board
Models reached through a hosted service. Claude Sonnet 5 is ranked by the highest-scoring of its 4 configurations: the 13th-highest score of 26 models, not clearly different from 5 other models. Scores are within 3 attempts (c@3) with 95% intervals; each configuration is compared with the highest-scoring one by whether their 95% intervals overlap. Every configuration on the board → Cost and speed →
- 95% interval
Show the numbers
| Configuration | Rank all configs | Within 3 attempts c@3 · 95% CI | Against the highest by 95% interval overlap | Tokens mean · median · p90 | No answer | Latency median per task, every attempt counted | Cost per task | Cost per solved task |
|---|---|---|---|---|---|---|---|---|
| Anthropic · highhighest score | 21 | 77%95% CI 73–81 | — | 2.4k978 · 7.2k | 0% | 11 s | $0.059 | $0.076 |
| Anthropic · medium | 24 | 75%95% CI 71–79 | not clearly different | 1.2k562 · 3.3k | 0% | 9.0 s | $0.034 | $0.045 |
| Anthropic · thinking off | 26 | 71%95% CI 67–76 | not clearly different | 919586 · 2.1k | 0% | 8.0 s | $0.023 | $0.032 |
| Anthropic · low | 28 | 69%95% CI 64–74 | not clearly different | 730408 · 2k | 0% | 5.8 s | $0.022 | $0.032 |
- 95% interval
- API board median
Show the numbers
| Suite | c@3 95% CI | API median | Tasks |
|---|---|---|---|
| Apex | 90%95% CI 70–97 | 90% | 20 |
| Salesforce APIs | 89%95% CI 67–97 | 72% | 18 |
| CI/CD | 76%95% CI 53–90 | 88% | 17 |
| Salesforce CLI | 90%95% CI 70–97 | 90% | 20 |
| Salesforce docs | 24%95% CI 10–47 | 29% | 17 |
| fflib Enterprise Patterns | 67%95% CI 44–84 | 61% | 18 |
| Flow | 100%95% CI 82–100 | 69% | 18 |
| Governor limits & pushback | 79%95% CI 57–91 | 89% | 19 |
| Lightning Web Components | 100%95% CI 82–100 | 100% | 18 |
| Nonprofit Success Pack | 83%95% CI 61–94 | 81% | 18 |
| Packaging | 72%95% CI 49–88 | 69% | 18 |
| Permissions & access | 80%95% CI 55–93 | 87% | 15 |
| Scratch org definitions | 50%95% CI 29–71 | 50% | 18 |
| SOQL | 100%95% CI 84–100 | 100% | 20 |
| Trigger Actions Framework | 56%95% CI 34–75 | 86% | 18 |
By reasoning effort
The same configuration at several efforts, each against its lowest reasoning effort on the same tasks (a paired 95% interval), and charted against the effort tier and against the output tokens it costs. These scores are pass@1, the first answer alone: a paired comparison needs both efforts' answers to the same tasks, and not every effort has had its retries. Lite-subset sweeps (4 tasks per suite) are never plotted with the full benchmark. The effort study has every model.
| Configuration · effort · full benchmark | pass@1 95% CI | Against the lowest reasoning effort same tasks, paired | Tokens |
|---|---|---|---|
| thinking off | 58%95% CI 52–63 | no clear difference (+3 pts, 95% CI −2 pts to +7 pts); this data can't rule out a change of up to 7 points | 919 |
| lowbaseline | 55%95% CI 50–61 | — | 730 |
| medium | 60%95% CI 55–65 | no clear difference (+5 pts, 95% CI ±0 pts to +9 pts); this data can't rule out a change of up to 9 points | 1.2k |
| high | 65%95% CI 60–70 | clearly higher (+10 pts, 95% CI +5 pts to +14 pts) | 2.4k |
Show the numbers
| Model | Effort (tier) | pass@1 | 95% CI | Tasks | No answer | Tokens: mean | median | Latency: median per answer |
|---|---|---|---|---|---|---|---|---|
| Claude Sonnet 5 | thinking off | 58% | 52–63 | 272 | 0% | 919 | 586 | 6.6 s |
| Claude Sonnet 5 | low | 55% | 50–61 | 272 | 0% | 730 | 408 | 5.0 s |
| Claude Sonnet 5 | medium | 60% | 55–65 | 272 | 0% | 1.2k | 562 | 7.2 s |
| Claude Sonnet 5 | high · vendor default | 65% | 60–70 | 272 | 0% | 2.4k | 978 | 9.8 s |
In the studies
- Reasoning effort: its score against effort and against output tokens.
- Local vs API: where it lands among the configurations of both boards.
- Pushback: whether it pushed back on requests that break at scale.
Private evaluations
Want this for your team?
Azul Labs runs Forcebench privately for two kinds of Salesforce team.
Choosing a model to run yourself?
A private benchmark of your shortlist
Open-weight models at the quantisations and reasoning efforts you could run on infrastructure you control, tested on your kind of Salesforce work, with a written recommendation.
- Private tasks written from your work only ever run on local models; they are never sent to an API.
- Re-testing after any change of model, quantisation or engine is available.
- Typical turnaround is 2–3 weeks; large models take about a day of machine time per configuration.
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A private evaluation of your tool
Your tool on held-out tasks it has never seen, against API baselines (models reached through a hosted service) and Local ones (served on Forcebench’s own hardware), with a written report on where it holds up and where it fails.
- It can start as a smaller pilot, about 30 held-out tasks with your tool against two baselines, before a full evaluation.
- Repeat evaluations after your releases are available.
- Typical turnaround is 2–3 weeks.
Fixed fee, quoted up front. The quote depends on the number of tasks and the number of models, tools or configurations tested.
Or email leo@azl.au · azl.au