Agentic
Not comparable- Celeris-1
- Not ranked
- Gemma 4 26B A4B
- 49.2
- Estimated · #71/151
- Basis
- BenchAlign lane · 0 vs 0 public rows
- Reading
- Not comparable
Celeris-1 vs Gemma 4 26B A4B
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Long documents
Prompts that approach the documented context limit
Gemma 4 26B A4B
Gemma 4 26B A4B has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Celeris-1 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Celeris-1 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Celeris-1 does not fit this workload in one request. Gemma 4 26B A4B has no comparable published API token rate.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Celeris-1 does not fit this workload in one request. Celeris-1 has no published cached-input rate, so cached tokens use its listed input rate. Gemma 4 26B A4B has no comparable published API token rate.
Confidence: rate-fallback
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Celeris-1 does not fit this workload in one request. Gemma 4 26B A4B has no comparable published API token rate.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
3 Celeris-1 only
1 Shared
3 Gemma 4 26B A4B only
- Shared results
- 1
- Celeris-1 only
- 3
- Gemma 4 26B A4B only
- 3
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
Coding
Not comparable- Celeris-1
- Not ranked
- Gemma 4 26B A4B
- 41.7
- Supported · #130/183
- Basis
- BenchAlign lane · 0 vs 0 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Celeris-1
- 47.8
- Unranked · 3 rankable rows
- Gemma 4 26B A4B
- 65.4
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Knowledge
Not comparable- Celeris-1
- Not ranked
- Gemma 4 26B A4B
- 44.1
- Supported · #120/181
- Basis
- BenchAlign lane · 1 vs 3 public rows
- Reading
- Not comparable
Math
Not comparable- Celeris-1
- Not ranked
- Gemma 4 26B A4B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Celeris-1
- Not ranked
- Gemma 4 26B A4B
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Celeris-1
- Not ranked
- Gemma 4 26B A4B
- 44.1
- #41/48
- Basis
- Provisional lane · 0 vs 1 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Celeris-1
- Not ranked
- Gemma 4 26B A4B
- 88.4
- #30/120
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Celeris-1 | Gemma 4 26B A4B | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | 49.2Estimated · #71/151 | Not comparableBenchAlign lane · 0 vs 0 public rows | Not comparable |
| Coding | Not ranked | 41.7Supported · #130/183 | Not comparableBenchAlign lane · 0 vs 0 public rows | Not comparable |
| Reasoning | 47.8Unranked · 3 rankable rows | 65.4Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | Not ranked | 44.1Supported · #120/181 | Not comparableBenchAlign lane · 1 vs 3 public rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | 44.1#41/48 | Not comparableProvisional lane · 0 vs 1 weighted rows | Not comparable |
| Instruction following | Not ranked | 88.4#30/120 | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
MMLU-Pro
Knowledge
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- Celeris-1
- $0.00055
- Does not fit in one request
- Gemma 4 26B A4B
- Self-hosted; infrastructure cost varies
- Fits in one request
Celeris-1 does not fit this workload in one request. Gemma 4 26B A4B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Celeris-1
- $0.0121
- Does not fit in one request
- Gemma 4 26B A4B
- Self-hosted; infrastructure cost varies
- Fits in one request
Celeris-1 does not fit this workload in one request. Gemma 4 26B A4B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Celeris-1
- $0.051
- Does not fit in one request
- Cached input priced at the published list-input rate
- Gemma 4 26B A4B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
Celeris-1 does not fit this workload in one request. Celeris-1 has no published cached-input rate, so cached tokens use its listed input rate. Gemma 4 26B A4B has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationCeleris-1Gemma 4 26B A4B
Context window
Maximum documented context; output-token limits may be lower.
Celeris-1
131,072 tokens
Celeris-1 model guideGemma 4 26B A4B
API model ID
Celeris-1
celeris-1
Celeris-1 model guideGemma 4 26B A4B
gemma-4-26b-a4b-it
Google Gemma Gemini API guideCached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Celeris-1
Not published
Celeris API pricingGemma 4 26B A4B
No comparable hosted API rate
Documented inputs
Celeris-1
text, image
Celeris-1 model guideGemma 4 26B A4B
text, image
Google Gemma 4 model documentationDocumented outputs
Celeris-1
Gemma 4 26B A4B
Provider availability
Celeris-1
Generally Available · Celeris OpenAI-compatible API (United States)
Celeris availabilityGemma 4 26B A4B
Generally Available · Gemini API, Google AI Studio, open weights
Google Gemma Gemini API guideReasoning profile
Celeris-1
Non-Reasoning
Gemma 4 26B A4B
Reasoning
Weight access
Celeris-1
Proprietary
Gemma 4 26B A4B
Open Weight
License
Celeris-1
Proprietary
Gemma 4 26B A4B
Open Weight
Release date
Celeris-1
2026-07-22
Gemma 4 26B A4B
2026-04-02
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Gemma 4 26B A4B has the larger documented window (256K).
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence7 rows
Reasoning
DROP
Celeris-181.4%SourceGemma 4 26B A4B—Not directly comparable
Knowledge
Math
GSM8K
Celeris-193.7%SourceGemma 4 26B A4B—Not directly comparable
Multimodal
MMMU-Pro
Celeris-1—Gemma 4 26B A4B73.8%SourceNot directly comparable
Instruction following
IFEval
Celeris-180.8%SourceGemma 4 26B A4B—Not directly comparable
Frequently asked questions
Which is better, Celeris-1 or Gemma 4 26B A4B?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Celeris-1 or Gemma 4 26B A4B?
Celeris-1 is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Celeris-1 or Gemma 4 26B A4B?
Celeris-1 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Celeris-1 or Gemma 4 26B A4B?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Celeris-1 or Gemma 4 26B A4B?
Gemma 4 26B A4B has the larger documented context window: 256K, compared with 131,072 tokens.
Related comparisons
Last updated September 4, 2026
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